Informative features of local field potential signals in primary visual cortex during natural image stimulation

Semantic category-based decoding of human brain activity using a Gabor-based model by estimating intracranial field potential range in temporal cortex

Predicting and decoding the recorded neural activity for visual stimuli is the topic of many studies. This prediction can be made by comparing the model's responses to different stimuli with the available recorded brain signal. The neural activities can be decoded then by finding the stimulus which has generated the nearest model's response to the recorded signal. In this study, a model is proposed which can estimate the response of human brain to images from different conceptual categories by inserting the visual stimuli as the model input after filtering by Gabor wavelets. This helped us to find each image's low level visual features. Afterward, the extracted image features were applied to the input of a curve fitting neural network. As the output, the range of intracranial field potential was estimated. This was performed separately for each pixel of the image. To evaluate the model's accuracy, two factors were used, namely the Pearson correlation and Normalized root mean square error. The results show that the proposed model can accurately estimate the brain's response to conceptual categories To decode the brain' activity based on the observed semantic category in each test observations by using of the model, we calculated the distance between the recorded signal and the model responses to all stimuli from different categories and assigned the category of the nearest model response to brain's response in that trial. To this end, a K-nearest neighbors classifier based on Euclidean distance was used. This leaded to a classification accuracy which was significantly higher than chance level. So, the proposed model can be used to decode the activity of the brain in response to the visual stimuli.

New uses of LFPs: Pathway-specific threads obtained through spatial discrimination

Local field potentials (LFPs) reflect the coordinated firing of functional neural assemblies during information coding and transfer across neural networks. As such, it was proposed that the extraordinary variety of cytoarchitectonic elements in the brain is responsible for the wide range of amplitudes and for the coverage of field potentials, which in most cases receive contributions from multiple pathways and populations. The influence of spatial factors overrides the bold interpretations of customary measurements, such as the amplitude and polarity, to the point that their cellular interpretation is one of the hardest tasks in Neurophysiology. Temporal patterns and frequency bands are not exclusive to pathways but rather, the spatial configuration of the voltage gradients created by each pathway is highly specific and may be used advantageously. Recent technical and analytical advances now make it possible to separate and then reconstruct activity for specific pathways. In this review, we discuss how spatial features specific to cells and populations define the amplitude and extension of LFPs, why they become virtually indecipherable when several pathways are co-activated, and then we present the recent advances regarding their disentanglement using spatial discrimination techniques. The pathway-specific threads of LFPs have a simple cellular interpretation, and the temporal fluctuations obtained can be applied to a variety of new experimental objectives and improve existing approaches. Among others, they facilitate the parallel readout of activity in several populations over multiple time scales correlating them with behavior. Also, they access information contained in irregular fluctuations, facilitating the testing of ongoing plasticity. In addition, they open the way to unravel the synaptic nature of rhythmic oscillations, as well as the dynamic relationships between multiple oscillatory activities. The challenge of understanding which waves belong to which populations, and the pathways that provoke them, may soon be overcome.