Stimulus information stored in lasting active and hidden network states is destroyed by network bursts

Abstract

In both humans and animals brief synchronizing bursts of epileptiform activity known as interictal epileptiform discharges (IEDs) can, even in the absence of overt seizures, cause transient cognitive impairments (TCI) that include problems with perception or short-term memory. While no evidence from single units is available, it has been assumed that IEDs destroy information represented in neuronal networks. Cultured neuronal networks are a model for generic cortical microcircuits, and their spontaneous activity is characterized by the presence of synchronized network bursts (SNBs), which share a number of properties with IEDs, including the high degree of synchronization and their spontaneous occurrence in the absence of an external stimulus. As a model approach to understanding the processes underlying IEDs, optogenetic stimulation and multielectrode array (MEA) recordings of cultured neuronal networks were used to study whether stimulus information represented in these networks survives SNBs. When such networks are optically stimulated they encode and maintain stimulus information for as long as one second. Experiments involved recording the network response to a single stimulus and trials where two different stimuli were presented sequentially, akin to a paired pulse trial. We broke the sequential stimulus trials into encoding, delay and readout phases and found that regardless of which phase the SNB occurs, stimulus-specific information was impaired. SNBs were observed to increase the mean network firing rate, but this did not translate monotonically into increases in network entropy. It was found that the more excitable a network, the more stereotyped its response was during a network burst. These measurements speak to whether SNBs are capable of transmitting information in addition to blocking it. These results are consistent with previous reports and provide baseline predictions concerning the neural mechanisms by which IEDs might cause TCI.

State-Dependent Propagation of Neuronal Sub-Population in Spontaneous Synchronized Bursts

“…Such hidden states could account for consecutive appearances of similar bursts and can be considered an internal memory of a neuronal network. This internal memory is likely stronger than the short-term memory of external events, which is easily broken by bursts; i.e., internal memory (Dranias et al, 2013 , 2015 ; Ju et al, 2015 ). Inhibitory interneurons may significantly contribute to selection of spatiotemporal patterns (Sasaki et al, 2014 ), depending on such hidden states.…”

“…Recently, cortical spontaneous activities were characterized as having multiple “metastable states” itinerating in an activity dependent manner (Mazzucato et al, 2015 ). A particular state should continue during a quiescent period (Dranias et al, 2013 , 2015 ; Ju et al, 2015 ) because cellular and synaptic properties governing states are likely to last without explicit spiking (Buonomano and Maass, 2009 ). Based on these studies, we hypothesize that (i) stable spatiotemporal patterns in synchronized spontaneous activity are generated by sequential activation of sub-populations, and that (ii) these patterns are generated in a state-dependent manner, whereby multiple metastable states can be defined as a finite continuous period.…”

Neurocomputational models of interval and pattern timing

“…The hypothesis is that each sensory event interacts with the current state of the network, forming a pattern of network states that naturally encodes each event in the context of the recent stimulus history—much as the ripples generated by each raindrop falling in a pond will interact with the ripples created by previous raindrops. Experimental studies have supported this hypothesis by demonstrating that cortical networks contain information about not only the current stimulus, but also the interval and order of recent events [60–64]. …”

Spatiotemporal Memory Is an Intrinsic Property of Networks of Dissociated Cortical Neurons

“…Our results provide experimental support to this idea, with one qualification: population spikes may not be necessary, as each input pattern activated only a subset of neurons, not the entire network. Indeed, as shown by the results from the APV treatment in the musical style classification task, excessive activity seen during a synchronized network burst is detrimental to information processing and may eradicate memory information residing in the networks (see also Dranias et al, 2015).…”