Sense-making, within enactive theories, provides a novel way of understanding how a comprehensible and manageable world arises for a subject. Elaboration of the concept of sense-making allows a fundamental reframing of the notion of perception that does not rely on the pick up of information about a pre-given world. In rejecting the notion of the subject as an input/output system, it is also necessary to reframe the scientific account of skilled action. Taking speech as an exemplary domain, I here present the outline of an enactive account of skilled action that is continuous with the concept of sense-making. Extending this account to the rich domain of joint or synchronous speaking allows many of the principal themes of the emerging enactive account to be considered as they relate to a familiar and important human practice.

Key words: synchronization, sense-making, speech, joint action, joint speaking.

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.

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 noninvasively an important part of cortical source locations and dynamic and, therefore, to reveal brain functional networks.

This article presents, for the first time, a practical method for the direct quantification of frequency-specific synchronization (i.e., transient phase-locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long-range neural integration during cognitive tasks. The method, called phase-locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time-resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large-scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long-scale effects do reflect cognitive processing, short-scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony.

Key words: neural synchrony, phase-locking, coherence, EEG, EcoG, epilepsy, gamma-band, deblurring

This paper studies gamma-band responses from two implanted epileptic patients during a simple visual discrimination task. Our main aim was to ascertain, in a reliable manner, whether evoked (stimulus-locked) and induced (triggered by, but not locked to, stimuli) responses are present in intracranial recordings. For this purpose, we introduce new methods adapted to detect the presence of gamma responses at this level of recording, intermediary between EEG-scalp and unicellular responses. The analysis relies on a trial-by-trial time–frequency analysis and on the use of surrogate data for statistical testing. We report that visual stimulation reliably elicits evoked and induced responses in human intracranial recordings. Induced intracranial gamma activity is significantly present in short oscillatory bursts (a few cycles) following visual stimulation. These responses are highly variable from trial to trial, beginning after 200 ms and lasting up to 500 ms. In contrast, intracranial-evoked gamma responses concentrate around 100 ms latencies corresponding to evoked responses observed on the scalp. We discuss our results in relation to scalp gamma response in a similar protocol [Tallon-Baudry et al. (1996) J. Neurosci., 16, 4240–4249] and draw some conclusions for bridging the gap between gamma oscillations observed on the scalp surface and their possible cortical sources.

Key words: human, gamma-band activity, intracortical recordings, phase synchronization, surrogate data, time-frequency analysis, visual discrimination

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.

Key words: phase synchrony, neural synchrony, Hilbert transform, wavelet transform, surrogate data

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.

Key words: EEG, ictogenesis, nonlinear analysis, seizure anticipation, synchronization

In this study we describe visually triggered gamma oscillations in the optic tectum of awake pigeons. This study was motivated by the potential relevance of synchronous oscillatory responses in perceptual binding in a laminated structure other than the mammalian neocortex. Tectal responses were recorded as local field potential and multiunit activity by differential filtering. The local field potential was analysed by computing its autocorrelation function and spectral power with a moving window applied to single response sweeps. The temporal structure of the spike trains was evaluated by computing averaged autocorrelograms. A damped sine wave function was fitted to the autocorrelograms in order to quantify the degree of oscillation of both signals. Epochs of significant oscillatory activity were observed in the local field potential in 60% of the trials (n= 39). In all trials, significant oscillations occupied ∼ 10% of the time the stimulus was present. The oscillatory events in both the local field potential and the multiunit activity had frequencies in the range of 20 – 50 Hz. It is important to emphasize the great variability in the frequency and in the probability of occurrence of the oscillatory responses from trial to trial, which makes the oscillatory behaviour of the tectal activity highly non-stationary. The oscillatory activity we describe in the avian tectum has characteristics similar to those reported in the mammalian neocortex. These findings from a fully awake animal strengthen the universality of oscillations as a possible carrier for synchronization of activity in the constitution of neuronal assemblies.

Key words: avian optic tectum, local field potential, multiunit activity, neuronal assemblies, oscillatory activity, temporal binding

Abstract Multiunit activity was recorded in the optic tectum of awake pigeons with two electrodes at sites varying in depth and separated by 0.3 to 3.0 mm. Autocorrelation and cross-correlation functions were computed from the recorded spike trains to determine temporal relationships in the neuronal firing patterns. Cross-correlation analysis revealed that spatially separate groups of cells in the tectum show synchronous responses to a visual stimulus. Strong synchronization occurred in both superficial and deep layers of the tectum, in general with zero-phase shift. The response synchronization in the avian optic tectum resembles that observed in the mammalian cortex, suggesting that it may subserve common functions in visual processing.

Key words: Temporal coding, Synchronization, Oscillation, Optic tectum, Pigeon

Transient periods of synchronization of oscillating neuronal discharges in the frequency range 30–80 Hz (gamma oscillations) have been proposed to act as an integrative mechanism that may bring a widely distributed set of neurons together into a coherent ensemble that underlies a cognitive act. Results of several experiments in animals provide support for this idea. In humans, gamma oscillations have been described both on the scalp (measured by electroencephalography and magnetoencephalography) and in intracortical recordings, but no direct participation of synchrony in a cognitive task has been demonstrated so far. Here we record electrical brain activity from subjects who are viewing ambiguous visual stimuli (perceived either as faces or as meaningless shapes). We show for the first time, to our knowledge, that only face perception induces a long-distance pattern of synchronization, corresponding to the moment of perception itself and to the ensuing motor response. A period of strong desynchronization marks the transition between the moment of perception and the motor response. We suggest that this desynchronization reflects a process of active uncoupling of the underlying neural ensembles that is necessary to proceed from one cognitive state to another.