Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

Riccardo Storchi,Gian Carlo Caramenti,Maurizio Valente,Gabriele E M Biella,Antonio G Zippo

doi:10.1371/journal.pone.0035850

Riccardo Storchi, Gian Carlo Caramenti + Show 3 more

Open Access

https://doi.org/10.1371/journal.pone.0035850

Copy DOI

Abstract

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

Highlights

Local Field Potentials (LFPs) and spikes represent two aspects of neural signalling, tightly combined in complex causal relations [1,2]
In the attempt to recognize a relation between the local network level (LFPs) and the single neuron activity, we first determined stimulus responsiveness of spikes and LFPs
The Mutual Information (MI) reaches its highest attainable value of 1 bit, when the spike count reduces to zero the uncertainty about stimulus occurrence

Summary

Introduction

Local Field Potentials (LFPs) and spikes represent two aspects of neural signalling, tightly combined in complex causal relations [1,2]. Since the first LFP-spike analyses, it has been possible to elucidate the spatial and temporal scales of synaptic input integration [3,4], to improve the readout of sensory stimuli [5,6] and to hypothesize efficient modalities of neuron-to-neuron communication between distant brain areas [7,8]. Only few attempts have been made to predict spike occurrence from LFP oscillations [9,10]. Neurons in S-I are known to integrate a complex signal packet of temporal and modal features with millisecond precision [11,12,13]

Objectives

Methods

Results

Conclusion