Identifying mesoscopic activity patterns in auditory category discrimination task

Abstract

The capability to discriminate stimulus categories is required for complex cognitive processes and it is a feature present in different organisms. In the case of Mongolian gerbils, it has been shown that their primary auditory cortex is necessary for the formation of auditory categories with FM sweeps [1], since after cortex ablation the animals are not able to discriminate these stimulus categories, although still capable of discriminating pure tones. This indicates that the formation of categories is reflected in neuronal activity in this cortical area. Moreover, spatiotemporal patterns have been shown to occur in recordings with surface electrodes (electrocorticogram or ECoG) at the mesoscopic local field potential (LFP) level [2], indicating such a category formation. We hypothesize that we can also identify patterns of neuronal unit activity pertaining to specific categories when the animals are performing auditory category discrimination tasks, both at the level of single units (spikes, microscopic) and at LFP level (mesoscopic).Here we present a study which also serves as the first step towards an upcoming optogenetics study where the behavior of the animal will be manipulated by optical stimulation. We show that indeed we were able to find behavior related marked states, albeit here in the LFP signal from deeply inserted electrodes as opposed to the former study with ECoG signal (surface electrodes). These marked states were first identified in [2] as specific trajectories of neuronal activities (derived from parallel ECoG data) in the high-dimensional space, each indicating a particular category of the auditory stimuli. The experiment consists, as in [2], of an auditory category discrimination task where Mongolian gerbils are presented with either ‘rising’ or ‘falling’ frequency modulated sweeps (GO or NO GO stimuli, respectively) in a shuttlebox paradigm. If the animal receives a GO stimulus, it should shuttle within 4 seconds, otherwise it is shocked until it does. Conversely, in a NO GO trial, it does not get shocked if it stays put for 4 seconds, but will be shocked if it incorrectly shuttles. Throughout the trials recordings of electrophysiological signals were performed with a custom made set of tetrodes (3-8). LFPs and spikes were extracted from the recorded signals. We analyzed parallel LFP recordings for marked states with the same method as proposed in [2] but newly implemented in Python to be compatible with the open source data analysis toolbox Elephant developed at INM-6 [3]. With this method we were able to reproduce prior findings [2] by detecting marked states, i.e. they differed substantially between trials of GO stimulus and NO GO stimulus. Our next goal is to test if we find similar states in the parallel spiking activities, e.g. in the form of spatio-temporal patterns [4]. Of particular interest will be if and how the marked states identified in the mesoscopic signals (LFP) relate to the states identified at the microscopic level (spike data)