Navegando por Autor "Pipa, Gordon"

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Extraction of network topology from multi-electrode recordings: is there a small-world effect?
(2011-02-07) Gerhard, Felipe; Pipa, Gordon; Lima, Bruss; Maciel, Sergio Tulio Neuenschwander; Gerstner, Wulfram
The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons’ self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks’ observed small-world‑ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings.
Mapping of Visual Receptive Fields by Tomographic Reconstruction
(2012) Pipa, Gordon; Chen, Zhe; Maciel, Sergio Tulio Neuenschwander; Lima, Bruss; Brown, Emery N.
The moving bar experiment is a classic paradigm for characterizing the receptive field (RF) properties of neurons in primary visual cortex (V1). Current approaches for analyzing neural spiking activity recorded from these experiments do not take into account the point-process nature of these data and the circular geometry of the stimulus presentation. We present a novel analysis approach to mapping V1 receptive fields that combines point-process generalized linear models (PPGLM) with tomographic reconstruction computed by filtered-back projection.We use the method to map the RF sizes and orientations of 251 V1 neurons recorded from two macaque monkeys during a moving bar experiment. Our crossvalidated goodness-of-fit analyses show that the PPGLM provides a more accurate characterization of spike train data than analyses based on rate functions computed by the methods of spike-triggered averages or firstorder Wiener-Volterra kernel. Our analysis leads to a new definition of RF size as the spatial area over which the spiking activity is significantly greater than baseline activity. Our approach yields larger RF sizes and sharper orientation tuning estimates. The tomographic reconstruction paradigm further suggests an efficient approach to choosing the number of directions and the number of trials per direction in designing moving bar experiments. Our results demonstrate that standard tomographic principles for image reconstruction can be adapted to characterize V1 RFs and that two fundamental properties, size and orientation, may be substantially different from what is currently reported.
A new look at gamma? High- (>60 Hz) g-band activity in cortical networks: Function, mechanisms and impairment
(2011) Uhlhaas, Peter J.; Pipa, Gordon; Maciel, Sergio Tulio Neuenschwander; Wibral, Michael; Singer, Wolf
g-band oscillations are thought to play a crucial role in information processing in cortical networks. In addition to oscillatory activity between 30 and 60 Hz, current evidence from electro- and magnetoencephalography (EEG/MEG) and local-field potentials (LFPs) has consistently shown oscillations >60 Hz (high g-band) whose function and generating mechanisms are unclear. In the present paper, we summarize data that highlights the importance of high g-band activity for cortical computations through establishing correlations between the modulation of oscillations in the 60e200 Hz frequency and specific cognitive functions. Moreover, we will suggest that high g-band activity is impaired in neuropsychiatric disorders, such as schizophrenia and epilepsy. In the final part of the paper, we will review physiological mechanisms underlying the generation of high g-band oscillations and discuss the functional implications of low vs. high g-band activity patterns in cortical networks.

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Navegando por Autor "Pipa, Gordon"