Binding by Asynchrony: The Neuronal Phase Code

Neurons display continuous subthreshold oscillations and discrete action potentials (APs). When APs are phase-locked to the subthreshold oscillation, we hypothesize they represent two types of information: the presence/absence of a sensory feature and the phase of subthreshold oscillation. If subthreshold oscillation phases are neuron-specific, then the sources of APs can be recovered based on the AP times. If the spatial information about the stimulus is converted to AP phases, then APs from multiple neurons can be combined into a single axon and the spatial configuration reconstructed elsewhere. For the reconstruction to be successful, we introduce two assumptions: that a subthreshold oscillation field has a constant phase gradient and that coincidences between APs and intracellular subthreshold oscillations are neuron-specific as defined by the “interference principle.” Under these assumptions, a phase-coding model enables information transfer between structures and reproduces experimental phenomenons such as phase precession, grid cell architecture, and phase modulation of cortical spikes. This article reviews a recently proposed neuronal algorithm for information encoding and decoding from the phase of APs (Nadasdy, 2009). The focus is given to the principles common across different systems instead of emphasizing system specific differences

Information Encoding and Reconstruction from the Phase of Action Potentials

Fundamental questions in neural coding are how neurons encode, transfer, and reconstruct information from the pattern of action potentials (APs) exchanged between different brain structures. We propose a general model of neural coding where neurons encode information by the phase of their APs relative to their subthreshold membrane oscillations. We demonstrate by means of simulations that AP phase retains the spatial and temporal content of the input under the assumption that the membrane potential oscillations are coherent across neurons and between structures and have a constant spatial phase gradient. The model explains many unresolved physiological observations and makes a number of concrete, testable predictions about the relationship between APs, local field potentials, and subthreshold membrane oscillations, and provides an estimate of the spatio-temporal precision of neuronal information processing

Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering

This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods

Context-dependent spatially periodic activity in the human entorhinal cortex

The spatially periodic activity of grid cells in the entorhinal cortex (EC) of the rodent, primate, and human provides a coordinate system that, together with the hippocampus, informs an individual of its location relative to the environment and encodes the memory of that location. Among the most defining features of grid-cell activity are the 60 degrees rotational symmetry of grids and preservation of grid scale across environments. Grid cells, however, do display a limited degree of adaptation to environments. It remains unclear if this level of environment invariance generalizes to human grid-cell analogs, where the relative contribution of visual input to the multimodal sensory input of the EC is significantly larger than in rodents. Patients diagnosed with nontractable epilepsy who were implanted with entorhinal cortical electrodes performing virtual navigation tasks to memorized locations enabled us to investigate associations between grid-like patterns and environment. Here, we report that the activity of human entorhinal cortical neurons exhibits adaptive scaling in grid period, grid orientation, and rotational symmetry in close association with changes in environment size, shape, and visual cues, suggesting scale invariance of the frequency, rather than the wavelength, of spatially periodic activity. Our results demonstrate that neurons in the human EC represent space with an enhanced flexibility relative to neurons in rodents because they are endowed with adaptive scalability and context dependency

Children and adults rely on different heuristics for estimation of durations

Abstract Time is a uniquely human yet culturally ubiquitous concept acquired over childhood and provides an underlying dimension for episodic memory and estimating durations. Because time, unlike distance, lacks a sensory representation, we hypothesized that subjects at different ages attribute different meanings to it when comparing durations; pre-kindergarten children compare the density of events, while adults use the concept of observer-independent absolute time. We asked groups of pre-kindergarteners, school-age children, and adults to compare the durations of an "eventful" and "uneventful" video, both 1-minute long but durations unknown to subjects. In addition, participants were asked to express the durations of both videos non-verbally with simple hand gestures. Statistical analysis has revealed highly polarized temporal biases in each group, where pre-kindergarteners estimated the duration of the eventful video as "longer." In contrast, the school-age group of children and adults claimed the same about the uneventful video. The tendency to represent temporal durations with a horizontal hand gesture was evident among all three groups, with an increasing prevalence with age. These results support the hypothesis that pre-kindergarten-age children use heuristics to estimate time, and they convert from availability to sampling heuristics between pre-kindergarten and school age

Perceptual decision influences V1 neuronal responses to ambiguous threedimensional objects

We studied spike responses of V1 superficial layer neurons in a perceptual decision task. A rhesus monkey was trained to hold fixation during presentations of a three-dimensional (structure-from-motion) object and to make a perceptual decisions in an alternative choice paradigm while extracellular responses were obtained by single electrode penetrations. The disparity of constituent dots was varied from trial-to-trial to render perceptually ambiguous or unambiguous objects. Neurons with modulated disparity responses were selected. We estimated the certainty at which the firing rate of a given V1 neuron would allow an ideal observer to predict the monkey's perceptual choice in the task. Neuronal responses to zero-disparity (ambiguous) objects were sorted according to the perceptual decision and the choice probability was determined for each neuron (Britten et al., 1996). Based on the sample of n>100 neurons the firing rate ROC curves showed significant bias from chance starting at 500 msec after the stimulus onset. The choice probability was different from 0.5 for the significant majority of cells. The long latency of the perceptual bias in the V1 responses suggests a feed-back from higher visual cortical areas including MT/MST that further raises the question of V1's involvement in perceptual awareness. (Supported by NEI and J.G. Boswell Professorship) Acknowledgments: We thank to Christof Koch and Melissa Saenz for useful discussion