Information-geometric measures estimate neural interactions during oscillatory brain states

Abstract

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

Three-dimensional computer graphic animations for studying social approach behaviour in medaka fish: Effects of systematic manipulation of morphological and motion cues

“…In another fish species, several visual features, such as shoal size [ 22 – 25 ], sex [ 24 , 25 ], familiarity [ 22 ], body colouration [ 26 , 27 ], and body size [ 22 , 28 , 29 ], affect the formation of fish shoals. Although previous studies have primarily focused on what role morphological features of visual cues have in the social approach behaviour, perception of visual motion is one of the most basic abilities of fish as well as other vertebrates [ 30 , 31 ]. We recently showed that visual motion cues play critical roles in the decision making of medaka in studies on hunting behaviour against the modelled motion of zooplanktons [ 32 ] and social approach behaviour induced by biological motion stimuli of conspecific fish [ 33 ].…”

Editorial: Towards an integrated approach to measurement, analysis and modeling of cortical networks

“…Nie et al ( 2014 ) make use of Information Geometry (IG), which is based on the expansion of the joint probability distribution of an N-neuron system. They used two measures, the single-IG measure and the pairwise IG-measure to examine the activity of simulated interconnected neurons that exhibit oscillations.…”

Geometry of basic statistical physics mapping

“…The interrelation of the geometry and certain statistical models has been considered too (see e.g. [10][11][12][13][14]).…”