In this article we present a new method for reconstructing three-dimensional ͑3D͒ images with cylindrical symmetry from their two-dimensional projections. The method is based on expanding the projection in a basis set of functions that are analytical projections of known well-behaved functions. The original 3D image can then be reconstructed as a linear combination of these well-behaved functions, which have a Gaussian-like shape, with the same expansion coefficients as the projection. In the process of finding the expansion coefficients, regularization is used to achieve a more reliable reconstruction of noisy projections. The method is efficient and computationally cheap and is particularly well suited for transforming projections obtained in photoion and photoelectron imaging experiments. It can be used for any image with cylindrical symmetry, requires minimal user's input, and provides a reliable reconstruction in certain cases when the commonly used Fourier-Hankel Abel transform method fails.

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Humans often change their beliefs or behavior due to the behavior or opinions of others. This study explored, with the use of human event-related potentials (ERPs), whether social conformity is based on a general performance-monitoring mechanism. We tested the hypothesis that conflicts with a normative group opinion evoke a feedback-related negativity (FRN) often associated with performance monitoring and subsequent adjustment of behavior. The experimental results show that individual judgments of facial attractiveness were adjusted in line with a normative group opinion. A mismatch between individual and group opinions triggered a frontocentral negative deflection with the maximum at 200 ms, similar to FRN. Overall, a conflict with a normative group opinion triggered a cascade of neuronal responses: from an earlier FRN response reflecting a conflict with the normative opinion to a later ERP component (peaking at 380 ms) reflecting a conforming behavioral adjustment. These results add to the growing literature on neuronal mechanisms of social influence by disentangling the conflict-monitoring signal in response to the perceived violation of social norms and the neural signal of a conforming behavioral adjustment.

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Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space-time, space-frequency, and space-time-frequency domains. Signal processing and information theoretic measures are considered, and linear and nonlinear methods are distinguished. A novel set of cross-time-frequency measures is introduced, including a cross-time-frequency phase synchronization measure.

Objective: MEG dipole localization of epileptic spikes is useful in epilepsy surgery for mapping the extent of abnormal cortex and to focus intracranial electrodes. Visually analyzing large amounts of data produces fatigue and error. Most automated techniques are based on matching of interictal spike templates or predictive filtering of the data and do not explicitly include source localization as part of the analysis. This leads to poor sensitivity versus specificity characteristics. We describe a fully automated method that combines time-series analysis with source localization to detect clusters of focal neuronal current generators within the brain that produce interictal spike activity.Methods: We first use an ICA (Independent Components Analysis) method to decompose the multichannel MEG data and identify those components that exhibit spike-like characteristics. From these detected spikes we then find those whose spatial topographies across the array are consistent with focal neural sources, and determine the foci of equivalent current dipoles and their associated time courses. We then perform a clustering of the localized dipoles based on distance metrics that takes into consideration both their locations and time courses. The final step of refinement consists of retaining only those clusters that are statistically significant. The average locations and time series from significant clusters comprise the final output of our method.Results and Significance: Data were processed from four patients with partial focal epilepsy. In all three subjects for whom surgical resection was performed, clusters were found in the vicinity of the resectioned area.Conclusion: The presented procedure is promising and likely to be useful to the physician as a more sensitive, automated and objective method to help in the localization of the interictal spike zone of intractable partial seizures. The final output can be visually verified by neurologists in terms of both the location and distribution of the dipole clusters and their associated time series. Due to the clinical relevance and demonstrated promise of this method, further investigation of this approach is warranted.

Back in 2012, Churchland and his colleagues proposed that “rotational dynamics”, uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland’s own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal sequence in peak firing rates exhibited by individual neurons, and (2) this sequence remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland’s data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.’s bold assessment that such rotations are related to “an unexpected yet surprisingly simple structure in the population response”, which “explains many of the confusing features of individual neural responses”. Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

Background Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal. Methods Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40–57 Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes. Results Both groups reported that decreased PCC activity corresponded with effortless awareness (P<0.0025 for each group), with high median confidence ratings (novices: 8 on a 0–10 Likert scale; experienced: 9). Both groups showed high moment-to-moment median correspondence ratings between PCC activity and subjective experience of effortless awareness (novices: 8, experienced: 9). Both groups were able to volitionally control the PCC signal in the direction associated with effortless awareness by practicing effortless awareness meditation (novices: median % of time =77.97, P=0.001; experienced: 89.83, P<0.0005). Conclusions These findings support the feasibility of using EEG neurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training.