Lack of systematic topographic difference between attention and reasoning beta correlates.

Based on previous evidence for individual-specific sets of cortical areas active during simple attention tasks, in this work we intended to perform within individual comparisons of task-induced beta oscillations between visual attention and a reasoning task. Since beta induced oscillations are not time-locked to task events and were first observed by Fourier transforms, in order to analyze the cortical topography of attention induced beta activity, we have previously computed corrected-latency averages based on spontaneous peaks of band-pass filtered epochs. We then used Independent Component Analysis (ICA) only to single out the significant portion of averaged data, above noise levels. In the present work ICA served as the main, exhaustive means for decomposing beta activity in both tasks, using 128-channel EEG data from 24 subjects. Given the previous observed similarity between tasks by visual inspection and by simple descriptive statistics, we now intended another approach: to quantify how much each ICA component obtained in one task could be explained by a linear combination of the topographic patterns from the other task in each individual. Our hypothesis was that the major psychological difference between tasks would not be reflected as important topographic differences within individuals. Results confirmed the high topographic similarity between attention and reasoning beta correlates in that few components in each individual were not satisfactorily explained by the complementary task, and if those could be considered "task-specific", their scalp distribution and estimated cortical sources were not common across subjects. These findings, along with those from fMRI studies preserving individual data and conventional neuropsychological and neurosurgical observations, are discussed in support of a new functional localization hypothesis: individuals use largely different sets of cortical association areas to perform a given task, but those individual sets do not change importantly across tasks that differ in major psychological processes.

Minor and unsystematic cortical topographic changes of attention correlates between modalities.

In this study we analyzed the topography of induced cortical oscillations in 20 healthy individuals performing simple attention tasks. We were interested in qualitatively replicating our recent findings on the localization of attention-induced beta bands during a visual task [1], and verifying whether significant topographic changes would follow the change of attention to the auditory modality. We computed corrected latency averaging of each induced frequency bands, and modeled their generators by current density reconstruction with Lp-norm minimization. We quantified topographic similarity between conditions by an analysis of correlations, whereas the inter-modality significant differences in attention correlates were illustrated in each individual case. We replicated the qualitative result of highly idiosyncratic topography of attention-related activity to individuals, manifested both in the beta bands, and previously studied slow potential distributions [2]. Visual inspection of both scalp potentials and distribution of cortical currents showed minor changes in attention-related bands with respect to modality, as compared to the theta and delta bands, known to be major contributors to the sensory-related potentials. Quantitative results agreed with visual inspection, supporting to the conclusion that attention-related activity does not change much between modalities, and whatever individual changes do occur, they are not systematic in cortical localization across subjects. We discuss our results, combined with results from other studies that present individual data, with respect to the function of cortical association areas.

Graph theoretical characterization and tracking of the effective neural connectivity during episodes of mesial temporal epileptic seizure.

Via a detailed case study of mesial temporal lobe epilepsy, we show that a method of determining the direction of information flow among signals is able to provide focal localization via the simultaneous analysis of multiple EEG channels. This determination is accomplished by representing information flow direction via directed graphs, where focal electrodes are associated with high observed rates of pertinence to strongly connected subgraphs. Further clinical support to this finding is provided by results for an additional 9 cases of focal epilepsy cases. The graph theoretical approach is a tool for describing and analyzing the effective connectivity dynamics behind epileptic seizures and may provide a common language for studying other complex dynamic relationships between neural structures.