Electrophysiological and firing properties of neurons: Categorizing soloists and choristers in primary visual cortex

Abstract

Visual processing in the cortex involves various aspects of neuronal properties such as morphological, electrophysiological and molecular. In particular, the neural firing pattern is an important indicator of dynamic circuitry within a neuronal population. Indeed, in microcircuits, neurons act as soloists or choristers wherein the characteristical activity of a 'soloist' differs from the firing pattern of a 'chorister'. Both cell types correlate their respective firing rate with the global populational activity in a unique way. In the present study, we sought to examine the relationship between the spike shape (thin spike neurons and broad spike neurons) of cortical neurons recorded from V1, their firing levels and their propensity to act as soloists or choristers. We found that thin spike neurons, which exhibited higher levels of firing, generally correlate their activity with the neuronal population (choristers). On the other hand, broad spike neurons showed lower levels of firing and demonstrated weak correlations with the assembly (soloists). A major consequence of the present study is: estimating the correlation of neural spike trains with their neighboring population is a predictive indicator of spike waveforms and firing level. Indeed, we found a continuum distribution of coupling strength ranging from weak correlation-strength (attributed to low-firing neurons) to high correlation-strength (attributed to high-firing neurons). The tendency to exhibit high- or low-firing is conducive to the spike shape of neurons. Our results offer new insights into visual processing by showing how high-firing rate neurons (mostly thin spike neurons) could modulate the neuronal responses within cell-assemblies.

Differential effect of anesthesia on visual cortex neurons with diverse population coupling

“…First, we classified neurons based on PC and FR values in 0% desflurane (i.e., wakefulness) using K-means clustering. This was different from previous studies in which neurons were classified by either PC or FR alone [4,[6][7][8]. Figure 1A…”

“…The spikes of individual neurons are constrained to population activity; they only fire when the population fires, reducing the chance for processing a diverse content of sensory information; in other words, information capacity of the neural network becomes very low [13]. Considering the fact that soloists respond to sensory stimuli in a selective and precise manner [4,6], one could surmise that the absence of the actively firing soloists in anesthesia could be responsible for the disruption of conscious sensory information processing. This proposition is consistent with anesthetic-related changes in large-scale brain activity such as electroencephalogram, which exhibits slow oscillation, low-frequency synchronization (0.1-5 Hz), or suppressed signal complexity as typical signatures of anesthetic-induced unconsciousness [14][15][16].…”

“…Previous studies were performed under different behavioral conditions such as waking [1,5,6], sleep [6,7], or under anesthesia [1,4]. No study to-date has investigated the dose-dependent effect of anesthesia on FR and PC properties in the same animal in a systematic manner.…”

The dendritic tree a mathematical integrator

“…This leads to the emergence of a new acquired stimulus. Figure 4 shows a typical response profile after plasticity; the initial response declines and the combination of the removal of inhibition and new excitatory afferences as shown in Figure 3 changes the selectivity of the neuron, as shown by many studies (3,15,18).…”

“…Moreover, neuron type-specific distinctions in orientation selectivity such as the relationship between the firing rate levels (burst-spiking or regular-spiking) and the degree of orientation selectivity could distinguish biophysical features orchestrating the dynamics of stimulus integration (2). The coupling strength of neurons with the neighboring population could also play a key role in information processing within a neuronal assembly (3,4).…”