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N A Laskaris

Publications and source records attributed to N A Laskaris.

4 recordsLinked to original sources

The human primary somatosensory cortex response contains components related to stimulus frequency and perception in a frequency discrimination task.

Somatosensory stimulation of primary somatosensory cortex (SI) using frequency discrimination offers a direct, well-defined and accessible way of studying cortical decisions at the locus of early input processing. Animal studies have identified and classified the neuronal responses in SI but they have not yet resolved whether during prolonged stimulation the collective SI response just passively reflects the input or actively participates in the comparison and decision processes. This question was investigated using tomographic analysis of single trial magnetoencephalographic data. Four right-handed males participated in a frequency discrimination task to detect changes in the frequency of an electrical stimulus applied to the right-hand digits 2+3+4. The subjects received approximately 600 pairs of stimuli with Stim1 always at 21 Hz, while Stim2 was either 21 Hz (50%) or varied from 22 to 29 Hz in steps of 1 Hz. Both stimuli were 1 s duration, separated by a 1 s interval of no stimulation. The left-SI was the most consistently activated area and showed the first activation peak at 35-48 ms after Stim1 onset and sustained activity during both stimulus periods. During the Stim2 period, we found that the left-SI activation started to differ significantly between two groups of trials (21 versus 26-29 Hz) within the first 100 ms and this difference was sustained and enhanced thereafter (approximately 600 ms). When only correct responses from the above two groups were used, the difference was even higher at later latencies (approximately 650 ms). For one subject who had enough trials of same perception to different input frequencies, e.g. responded 21 Hz to Stim2 at 21 Hz (correct) and 26-29 Hz (error), we found the sustained difference only before 650 ms. Our results suggest that SI is involved with the analysis of an input frequency and related to perception and decision at different latencies.

Adult↗

Single-trial variability in early visual neuromagnetic responses: an explorative study based on the regional activation contributing to the N70m peak.

Cortical activity evoked by repeated identical sensory stimulation is extremely variable. The source of this variability is often assigned to "random ongoing background activity" which is considered to be irrelevant to the processing of the stimuli and can therefore be eliminated by ensemble averaging. In this work, we studied the single-trial variability in neuromagnetic responses elicited by circular checkerboard pattern stimuli with radii of 1.8 degrees, 3.7 degrees, and 4.5 degrees. For most of the MEG sensors over the occipital areas, the averaged signal showed a clear early (N70m) response following the stimulus onset and this response was modulated by the checkerboard size. A data-driven spatial filter was used to extract one of the many possible composite time courses of single-trial activity corresponding to the complex of N70m generators. Pattern analysis principles were then employed to analyze, classify, and handle the extracted temporal patterns. We explored whether these patterns correspond to distinct response modes, which could characterize the evoked response better than the averaged signal and over an extended range of latencies around N70m. A novel scheme for detecting and organizing the structure in single-trial recordings was utilized. This served as a basis for comparisons between runs with different checkerboard sizes and provided a causal interpretation of variability in terms of regional dynamics, including the relatively weak activation in primary visual cortex. At the level of single trial activity, the polymorphic response to a simple stimulus is generated by a coupling of polymodal areas and cooperative activity in striate and extrastriate areas. Our results suggest a state-dependent response with a wide range of characteristic time scales and indicate the ongoing activity as a marker of the responsiveness state.

Adult↗

Semantic geodesic maps: a unifying geometrical approach for studying the structure and dynamics of single trial evoked responses.

OBJECTIVES: A general framework for identifying and describing structure in a given sample of evoked response single-trial signals (STs) is introduced. The approach is based on conceptually simple geometrical ideas and enables the convergence of pattern analysis and non-linear time series analysis. METHODS: Classical steps for analyzing the STs by waveform are first employed and the ST-analysis is transferred to a multidimensional space, the feature space, the geometry of which is systematically studied via multidimensional scaling (MDS) techniques giving rise to semantic maps. The structure in the feature space characterizes the trial-to-trial variability and this is utilized to probe functional connectivity between two brain areas. The underlying dynamic process responsible for the emerged structure can be described by a multidimensional trajectory in the feature space. This in turn enables the detection of dynamical interareal coupling as similarity between the corresponding trajectories. RESULTS AND CONCLUSIONS: The utility of semantic maps was demonstrated using magnetoencephalographic data from a simple auditory paradigm. The coupling of ongoing activity and evoked response is vividly demonstrated and contrasted with the apparent deflection from zero baseline that survives averaging. Prototypes are easily identified as the end points of distinct paths in the semantic map representation, and their neighborhood is populated by STs with distinct properties not only in the latencies where the evoked response is expected to be strong, but also and very significantly in the prestimulus period. Finally our results provide evidence for interhemispheric binding in the (4-8 Hz) range and dynamical coupling at faster time scales.

Brain Mapping↗

Exploratory data analysis of evoked response single trials based on minimal spanning tree.

OBJECTIVE: An exploratory data analysis framework, based on minimal spanning tree, is proposed as a means to support the analysis of single trial (ST) electrophysiological signals. The core of this framework is the compact description of the input ST sample in a form of content-dependent ordered lists. Based on the established hierarchies, efficient ways to increase the SNR, extract prototypical responses, visualize possible self-organization trends in the sample and track the course of evoked response along the trial-to-trial dimension, are proposed. METHOD: Magnetoencephalographic auditory evoked responses were used for demonstrating and validating the introduced framework. RESULTS AND CONCLUSION: The results demonstrate the benefits, from this intelligent manipulation of STs, in understanding and enhancing the actual evoked signal. Specifically we find support for stimulus-induced phase-resetting hypothesis in the 3-20 Hz band, the existence of trials void of the prototypical evoked response, and an order across the single trial set hinting at an underlying process with long time scale.

Adult↗