Francisco J. Varela

SickKids, Toronto, Ontario, Canada

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Publications (82)470.85 Total impact

  • FRANCISCO J. VARELA
    Annals of the New York Academy of Sciences 02/2006; 879(1):143 - 153. · 4.38 Impact Factor
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    ABSTRACT: We present here ongoing patterns of distributed brain synchronous activity that correlate with the spontaneous flow of perceptual dominance during binocular rivalry. Specific modulation of the magnetoencephalographic (MEG) response evoked during conscious perception of a frequency-tagged stimulus was evidenced throughout rivalry. Estimation of the underlying cortical sources revealed, in addition to strong bilateral striate and extrastriate visual cortex activation, parietal, temporal pole and frontal contributions. Cortical activity was significantly modulated concomitantly to perceptual alternations in visual cortex, medial parietal and left frontal regions. Upon dominance, coactivation of occipital and frontal regions, including anterior cingulate and medial frontal areas, was established. This distributed cortical network, as measured by phase synchrony in the frequency tag band, was dynamically modulated in concert with the perceptual dominance of the tagged stimulus. While the anteroposterior pattern was recurrent through subjects, individual variations in the extension of the network were apparent.
    NeuroImage 10/2004; 23(1):128-40. · 6.25 Impact Factor
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    ABSTRACT: We applied a new method of imaging frequency-specific changes in brain activity in humans during a finger brushing task in order to measure changes in cortical rhythms during tactile stimulation. Neuromagnetic recordings were conducted in five subjects using a whole-head MEG system during tactile stimulation of the right index finger, with or without visual feedback, and while viewing another individual's index finger being stimulated. Volumetric images of changes in source power relative to pre-stimulus baseline levels were computed with 2 mm resolution over the entire brain using a minimum-variance beamforming algorithm (synthetic aperture magnetometry). Onset of tactile stimulation produced a brief (200-300 ms) suppression of mu band (8-15 Hz) and beta band (15-30 Hz) cortical activity in the primary somatosensory and primary motor cortex, respectively, followed by a bilateral increase in beta band activity ('beta rebound') in motor cortex. This pattern of suppression/rebound was absent when subjects observed finger brushing or brushing motions without receiving stimulation. In contrast, these conditions resulted in bilateral increases in beta band activity in sensorimotor areas and decreased power in the alpha (8-12 Hz) band in primary visual areas. These results show that spatially filtered MEG provides a useful method for directly imaging the temporal sequence of changes in cortical rhythms during transient tactile stimulation, and provide evidence that observation of tactile input to another individual's hand, or object motion itself, can influence independent rhythmic activity in visual and sensorimotor cortex.
    Cognitive Brain Research 11/2003; 17(3):599-611. · 3.77 Impact Factor
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    ABSTRACT: Although considerable information on cellular and network mechanisms of epilepsy exists, it is still not understood why, how, and when the transition from interictal to ictal state takes place. The authors review their work on nonlinear EEG analysis and provide consistent evidences that dynamical changes in the neural activity allows the characterization of a preictal state several minutes before seizure onset. This new neurodynamical approach of ictogenesis opens new perspectives for studying the basic mechanisms in epilepsy as well as for possible therapeutic interventions.
    Epilepsia 02/2003; 44 Suppl 12:30-43. · 3.91 Impact Factor
  • Olivier David, Line Garnero, Diego Cosmelli, Francisco J Varela
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    ABSTRACT: There is a growing interest in elucidating the role of specific patterns of neural dynamics--such as transient synchronization between distant cell assemblies--in brain functions. Magnetoencephalography (MEG)/electroencephalography (EEG) recordings consist in the spatial integration of the activity from large and multiple remotely located populations of neurons. Massive diffusive effects and poor signal-to-noise ratio (SNR) preclude the proper estimation of indices related to cortical dynamics from nonaveraged MEG/EEG surface recordings. Source localization from MEG/EEG surface recordings with its excellent time resolution could contribute to a better understanding of the working brain. We propose a robust and original approach to the MEG/EEG distributed inverse problem to better estimate neural dynamics of cortical sources. For this, the surrogate data method is introduced in the MEG/EEG inverse problem framework. We apply this approach on nonaveraged data with poor SNR using the minimum norm estimator and find source localization results weakly sensitive to noise. Surrogates allow the reduction of the source space in order to reconstruct MEG/EEG data with reduced biases in both source localization and time-series dynamics. Monte Carlo simulations and results obtained from real MEG data indicate it is possible to estimate non invasively an important part of cortical source locations and dynamic and, therefore, to reveal brain functional networks.
    IEEE Transactions on Biomedical Engineering 10/2002; 49(9):975-87. · 2.35 Impact Factor
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    ABSTRACT: This paper introduces the use of wavelet analysis to follow the temporal variations in the coupling between oscillatory neural signals. Coherence, based on Fourier analysis, has been commonly used as a first approximation to track such coupling under the assumption that neural signals are stationary. Yet, stationary neural processing may be the exception rather than the rule. In this context, the recent application to physical systems of a wavelet-based coherence, which does not depend on the stationarity of the signals, is highly relevant. This paper fully develops the method of wavelet coherence and its statistical properties so that it can be practically applied to continuous neural signals. In realistic simulations, we show that, in contrast to Fourier coherence, wavelet coherence can detect short, significant episodes of coherence between non-stationary neural signals. This method can be directly applied for an 'online' quantification of the instantaneous coherence between two signals.
    Neurophysiologie Clinique/Clinical Neurophysiology 07/2002; 32(3):157-74. · 2.55 Impact Factor
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    ABSTRACT: The transition of brain activity towards an epileptic seizure is still a poorly understood phenomenon. Dynamic changes in brain activity have been detected several minutes before seizure emergence in populations of patients with mesial temporal lobe epilepsy (MTLE), using non-linear analysis of intracranial EEG recordings. Similar detection of a pre-ictal state has been obtained with standard scalp EEG recordings using a modified non-linear method. Here we applied this strategy to the seizures of patients with neocortical partial epilepsy. Results obtained by non-linear similarity analysis of 41 seizures from 11 patients with refractory partial epilepsy originating from various sites of the neocortex showed that (i) a pre-ictal state was detected in 90% of the patients and in 83% of the seizures whatever their location, with a mean anticipation time of 7.5 min; (ii) similar pre-ictal dynamic changes were detected when non-linear analysis methods were applied to either intracranial or scalp EEG recordings; (iii) the recording sites exhibiting these pre-ictal changes were distributed both within the epileptogenic focus and at remote locations; (iv) most pre-ictal dynamic changes were not correlated with linear changes in the frequency spectrum or with changes in the visually inspected EEG and the patients' behaviour. Hypotheses on the neuronal mechanisms underlying the pre-ictal period are discussed. The present results, together with those recently obtained in an MTLE population, suggest that changes in pre-ictal dynamics are a general phenomenon associated with seizure emergence in a wide population of patients with partial epilepsy, wherever the epileptogenic focus is located. The possibility of anticipating the onset of seizures has considerable therapeutic implications.
    Brain 04/2002; 125(Pt 3):640-55. · 10.23 Impact Factor
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    ABSTRACT: Even during well-calibrated cognitive tasks, successive brain responses to repeated identical stimulations are highly variable. The source of this variability is believed to reside mainly in fluctuations of the subject's cognitive "context" defined by his/her attentive state, spontaneous thought process, strategy to carry out the task, and so on... As these factors are hard to manipulate precisely, they are usually not controlled, and the variability is discarded by averaging techniques. We combined first-person data and the analysis of neural processes to reduce such noise. We presented the subjects with a three-dimensional illusion and recorded their electrical brain activity and their own report about their cognitive context. Trials were clustered according to these first-person data, and separate dynamical analyses were conducted for each cluster. We found that (i) characteristic patterns of endogenous synchrony appeared in frontal electrodes before stimulation. These patterns depended on the degree of preparation and the immediacy of perception as verbally reported. (ii) These patterns were stable for several recordings. (iii) Preparatory states modulate both the behavioral performance and the evoked and induced synchronous patterns that follow. (iv) These results indicated that first-person data can be used to detect and interpret neural processes.
    Proceedings of the National Academy of Sciences 03/2002; 99(3):1586-91. · 9.81 Impact Factor
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    Andreas Weber, Francisco J. Varela
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    ABSTRACT: This paper proposes a basic revision of the understanding of teleology in biological sciences. Since Kant, it has become customary to view purposiveness in organisms as a bias added by the observer; the recent notion of teleonomy expresses well this as-if character of natural purposes. In recent developments in science, however, notions such as self-organization (or complex systems) and the autopoiesis viewpoint, have displaced emergence and circular self-production as central features of life. Contrary to an often superficial reading, Kant gives a multi-faceted account of the living, and anticipates this modern reading of the organism, even introducing the term self-organization for the first time. Our re-reading of Kant in this light is strengthened by a group of philosophers of biology, with Hans Jonas as the central figure, who put back on center stage an organism-centered view of the living, an autonomous center of concern capable of providing an interior perspective. Thus, what is present in nuce in Kant, finds a convergent development from this current of philosophy of biology and the scientific ideas around autopoeisis, two independent but parallel developments culminating in the 1970s. Instead of viewing meaning or value as artifacts or illusions, both agree on a new understanding of a form of immanent teleology as truly biological features, inevitably intertwined with the self-establishment of an identity which is the living process.
    Phenomenology and the Cognitive Sciences 01/2002; 1(2):97-125.
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    Evan Thompson, Francisco J. Varela
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    ABSTRACT: We propose a new approach to the neuroscience of consciousness, growing out of the 'enactive' viewpoint in cognitive science. This approach aims to map the neural substrates of consciousness at the level of large-scale, emergent and transient dynamical patterns of brain activity (rather than at the level of particular circuits or classes of neurons), and it suggests that the processes crucial for consciousness cut across the brain-body-world divisions, rather than being brain-bound neural events. Whereas standard approaches to the neural correlates of consciousness have assumed a one-way causal-explanatory relationship between internal neural representational systems and the contents of consciousness, our approach allows for theories and hypotheses about the two-way or reciprocal relationship between embodied conscious states and local neuronal activity.
    Trends in Cognitive Sciences 11/2001; 5(10):418-425. · 16.01 Impact Factor
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    ABSTRACT: The quantification of phase synchrony between neuronal signals is of crucial importance for the study of large-scale interactions in the brain. Two methods have been used to date in neuroscience, based on two distinct approaches which permit a direct estimation of the instantaneous phase of a signal [Phys. Rev. Lett. 81 (1998) 3291; Human Brain Mapping 8 (1999) 194]. The phase is either estimated by using the analytic concept of Hilbert transform or, alternatively, by convolution with a complex wavelet. In both methods the stability of the instantaneous phase over a window of time requires quantification by means of various statistical dependence parameters (standard deviation, Shannon entropy or mutual information). The purpose of this paper is to conduct a direct comparison between these two methods on three signal sets: (1) neural models; (2) intracranial signals from epileptic patients; and (3) scalp EEG recordings. Levels of synchrony that can be considered as reliable are estimated by using the technique of surrogate data. Our results demonstrate that the differences between the methods are minor, and we conclude that they are fundamentally equivalent for the study of neuroelectrical signals. This offers a common language and framework that can be used for future research in the area of synchronization.
    Journal of Neuroscience Methods 11/2001; 111(2):83-98. · 2.11 Impact Factor
  • Francisco J. Varela
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    ABSTRACT: that Varela and Maturana, now colleagues at the University of Chile, formulated their famous theory of autopoiesis (Maturana & Varela, 1973; 1980; see Varela, 1996a, for a personal recounting of this time and work). According to this theory, living systems are autonomous systems (endogenously controlled and self-organizing), and the minimal form of autonomy necessary and sufficient for characterizing biological life is autopoiesis, i.e., self-production having the form of an operationally closed, membrane-bounded, reaction network. Maturana and Varela also held that autopoiesis defines cognition in its minimal biological form as the `sense-making' capacity of life; and that the nervous system, as a result of the autopoiesis of its component neurons, is not an input-output information processing system, but rather an autonomous, Journal of Consciousness Studies, 8, No. 8, 2001, pp. 66--69 operationally closed network, whose basic f
    Trends in Cognitive Sciences 10/2001; · 16.01 Impact Factor
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    ABSTRACT: The quantification of phase synchrony between neuronal signals is of crucial importance for the study of large-scale interactions in the brain. Two methods have been used to date in neuroscience, based on two distinct approaches which permit a direct estimation of the instantaneous phase of a signal [Phys. Rev. Lett. 81 (1998) 3291; Human Brain Mapping 8 (1999) 194]. The phase is either estimated by using the analytic concept of Hilbert transform or, alternatively, by convolution with a complex wavelet. In both methods the stability of the instantaneous phase over a window of time requires quantification by means of various statistical dependence parameters (standard deviation, Shannon entropy or mutual information). The purpose of this paper is to conduct a direct comparison between these two methods on three signal sets: (1) neural models; (2) intracranial signals from epileptic patients; and (3) scalp EEG recordings. Levels of synchrony that can be considered as reliable are estimated by using the technique of surrogate data. Our results demonstrate that the differences between the methods are minor, and we conclude that they are fundamentally equivalent for the study of neuroelectrical signals. This offers a common language and framework that can be used for future research in the area of synchronization.
    Journal of Neuroscience Methods. 09/2001;
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    ABSTRACT: The study of dynamic changes in neural activity preceding epileptic seizure allows the characterization of a preictal state several minutes before seizure onset. This opens up new perspectives for studying the mechanisms of epileptogenesis as well as for possible therapeutic interventions, which represent a major breakthrough. In this review the authors present and discuss the results from their group in this domain using nonlinear analysis of brain signals, as well as the limitations of this topic and current questions.
    Journal of Clinical Neurophysiology 06/2001; 18(3):191-208. · 1.45 Impact Factor
  • Olivier David, Line Garnero, Francisco Varela
    NeuroImage 06/2001; 13(6):105-105. · 6.25 Impact Factor
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    ABSTRACT: The emergence of a unified cognitive moment relies on the coordination of scattered mosaics of functionally specialized brain regions. Here we review the mechanisms of large-scale integration that counterbalance the distributed anatomical and functional organization of brain activity to enable the emergence of coherent behaviour and cognition. Although the mechanisms involved in large-scale integration are still largely unknown, we argue that the most plausible candidate is the formation of dynamic links mediated by synchrony over multiple frequency bands.
    Nature reviews. Neuroscience 05/2001; 2(4):229-39. · 31.38 Impact Factor
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    ABSTRACT: New methods derived from non-linear analysis of intracranial recordings permit the anticipation of an epileptic seizure several minutes before the seizure. Nevertheless, anticipation of seizures based on standard scalp electroencephalographical (EEG) signals has not been reported yet. The accessibility to preictal changes from standard EEGs is essential for expanding the clinical applicability of these methods. We analysed 26 scalp-EEG/video recordings, from 60 min before a seizure, in 23 patients with temporal-lobe epilepsy. For five patients, simultaneous scalp and intracranial EEG recordings were assessed. Long-term changes before seizure onset were identified by a measure of non-linear similarity, which is very robust in spite of large artifacts and runs in real-time. In 25 of 26 recordings, measurement of non-linear changes in EEG signals allowed the anticipation of a seizure several minutes before it occurred (mean 7 min). These preictal changes in the scalp EEG correspond well with concurrent changes in depth recordings. Scalp-EEG recordings retain sufficient dynamical information which can be used for the analysis of preictal changes leading to seizures. Seizure anticipation strategies in real-time can now be envisaged for diverse clinical applications, such as devices for patient warning, for efficacy of ictal-single photon emission computed tomography procedures, and eventual treatment interventions for preventing seizures.
    The Lancet 02/2001; 357(9251):183-8. · 39.21 Impact Factor
  • Jack Foucher, Laurent Soufflet, Francisco Varela
    NeuroImage 01/2001; 13(6):668-668. · 6.25 Impact Factor
  • Olivier David, Line Garnero, Francisco J. Varela
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    ABSTRACT: Little has been done yet to study the synchronization properties of the sources estimated from the MEG/EEG inverse problem, despite the growing interest in the role of phase relations in brain functions. In order to achieve this aim, we propose a novel approach to the MEG/EEG inverse problem based on some regularization using spectral priors: The MEG/EEG raw data are filtered in a frequency band of interest and blurred with some specific “regularization noise” prior to the inversion process. This formalism uses non quadratic regularization and a deterministic optimization algorithm. We proceed to Monte Carlo simulations using the chaotic Rössler oscillators to model the neural generators. Our results demonstate that it is possible to reveal some phase-locking between brain sources with great accuracy following the computation of the inverse problem based on scalp MEG/EEG measurements.
    Information Processing in Medical Imaging, 17th International Conference, IPMI 2001, Davis, CA, USA, June 18-22, 2001, Proceedings; 01/2001
  • Antoine Lutz, Francisco Varela
    NeuroImage 01/2001; 13(6):330-330. · 6.25 Impact Factor

Publication Stats

9k Citations
470.85 Total Impact Points

Institutions

  • 2003
    • SickKids
      • Department of Diagnostic Imaging
      Toronto, Ontario, Canada
  • 2002
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
    • Humboldt-Universität zu Berlin
      Berlín, Berlin, Germany
  • 2001
    • York University
      Toronto, Ontario, Canada
  • 1991–1999
    • Pierre and Marie Curie University - Paris 6
      • • Centre de Recherche de l'Institut du Cerveau et de la Moelle Epinière
      • • Laboratoire de Neurosciences cognitives et imagerie cérébrale (UPR 640)
      Paris, Ile-de-France, France
  • 1996–1997
    • Max Planck Institute for Brain Research
      Frankfurt, Hesse, Germany
  • 1993
    • École des Neurosciences de Paris Île-de-France
      Lutetia Parisorum, Île-de-France, France
  • 1988
    • University of Chile
      • Departamento de Biología
      Santiago, Region Metropolitana de Santiago, Chile
  • 1982–1987
    • University of Santiago, Chile
      • Facultad de Ciencia
      CiudadSantiago, Santiago, Chile