Brain Topography 

About: Brain Topography is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Electroencephalography & Medicine. It has an ISSN identifier of 0896-0267. Over the lifetime, 1489 publications have been published receiving 55227 citations.

Topographic ERP Analyses: A Step-by-Step Tutorial Review

Abstract: In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation.

Abstract: Background The International 10-20 system for EEG electrode placement is increasingly applied for the positioning of transcranial magnetic stimulation (TMS) in cognitive neuroscience and in psychiatric treatment studies. The crucial issue in TMS studies remains the reliable positioning of the coil above the skull for targeting a desired cortex region. In order to asses the precision of the 10-20 system for this purpose, we tested its projections onto the underlying cortex by using neuronavigation. Methods In 21 subjects, the 10-20 positions F3, F4, T3, TP3, and P3, as determined by a 10-20 positioning cap, were targeted stereotactically. The corresponding individual anatomical sites were identified in the Talairach atlas. Results The main targeted regions were: for F3 Brodmann areas (BA) 8/9 within the dorsolateral prefrontal cortex, for T3 BA 22/42 on the superior temporal gyrus, for TP3 BA 40/39 in thearea of the supramarginal and angular gyrus, and for P3 BA 7/40 on the inferior parietal lobe. However, in about 10% of the measurements adjacent and possibly functionally distinct BAs were reached. The ranges were mainly below 20 mm. Conclusion Using the 10-20 system for TMS positioning is applicable at low cost and may reach desired cortex regions reliably on a larger scale level. For finer grained positioning, possible interindividual differences, and therefore the application of neuroimaging based methods, are to be considered.

Mu and beta rhythm topographies during motor imagery and actual movements.

Abstract: People can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topographies associated with actual hand movement to those associated with imagined hand movement. Sixty-four EEG channels were recorded while each of 33 adults moved left- or right-hand or imagined doing so. Frequency-specific differences between movement or imagery and rest, and between right- and left-hand movement or imagery, were evaluated by scalp topographies of voltage and r spectra, and principal component analysis. Both movement and imagery were associated with mu and beta rhythm desynchronization. The mu topographies showed bilateral foci of desynchronization over sensorimotor cortices, while the beta topographies showed peak desynchronization over the vertex. Both mu and beta rhythm left/right differences showed bilateral central foci that were stronger on the right side. The independence of mu and beta rhythms was demonstrated by differences for movement and imagery for the subjects as a group and by principal components analysis. The results indicated that the effects of imagery were not simply an attenuated version of the effects of movement. They supply evidence that motor imagery could play an important role in EEG-based communication, and suggest that mu and beta rhythms might provide independent control signals.

Suppression of interference and artifacts by the Signal Space Separation Method.

Abstract: Multichannel measurement with hundreds of channels oversamples a curl-free vector field, like the magnetic field in a volume free of sources. This is based on the constraint caused by the Laplace's equation for the magnetic scalar potential; outside of the source volume the signals are spatially band limited. A functional solution of Laplace's equation enables one to separate the signals arising from the sphere enclosing the interesting sources, e.g. the currents in the brain, from the magnetic interference. Signal space separation (SSS) is accomplished by calculating individual basis vectors for each term of the functional expansion to create a signal basis covering all measurable signal vectors. Because the SSS basis is linearly independent for all practical sensor arrangements, any signal vector has a unique SSS decomposition with separate coefficients for the interesting signals and signals coming from outside the interesting volume. Thus, SSS basis provides an elegant method to remove external disturbances. The device-independent SSS coefficients can be used in transforming the interesting signals to virtual sensor configurations. This can also be used in compensating for distortions caused by movement of the object by modeling it as movement of the sensor array around a static object. The device-independence of the decomposition also enables physiological DC phenomena to be recorded using voluntary head movements. When used with properly designed sensor array, SSS does not affect the morphology or the signal-to-noise ratio of the interesting signals.

Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures

Abstract: Summary: Electrocorticograms (ECoG's) from 16 of 68 chronically implanted subdural electrodes, placed over the right temporal cortex in a patient with a right medial temporal focus, were analyzed using methods from nonlinear dynamics. A time series provides information about a large number of pertinent variables, which may be used to explore and characterize the system's dynamics. These variables and their evolution in time produce the phase portrait of the system. The phase spaces for each of 16 electrodes were constructed and from these the largest average Lyapunov exponents (L's), measures of chaoticity of the system (the larger the L, the more chaotic the system is), were estimated over time for every electrode before, in and after the epileptic seizure for three seizures of the same patient. The start of the seizure corresponds to a simultaneous drop in L values obtained at the electrodes nearest the focus. L values for the rest of the electrodes follow. The mean values of L for all electrodes in the postictal state are larger than the ones in the preictal state, denoting a more chaotic state postictally. The lowest values of L occur during the seizure but they are still positive denoting the presence of a chaotic attractor. Based on the procedure for the estimation of L we were able to develop a methodology for detecting prominent spikes in the ECoG. These measures (L*) calculated over a period of time (10 minutes before to 10 minutes after the seizure outburst) revealed a remarkable coherence of the abrupt transient drops of L* for the electrodes that showed the inital ictal onset. The L* values for the electrodes away from the focus exhibited less abrupt transient drops. These results indicate that the largest average Lyapunov exponent L can be useful in seizure detection as well as a discriminatory factor for focus localization in multielectrode analysis.