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Summary The auditory midbrain (inferior colliculus, IC) plays an important role in sound processing, acting as hub for acoustic information extraction and for the implementation of fast audio-motor behaviors. IC neurons are topographically organized according to their sound frequency preference: dorsal IC regions encode low frequencies while ventral areas respond best to high frequencies, a type of sensory map defined as tonotopy. Tonotopic maps have been studied extensively using artificial stimuli (pure tones) but our knowledge of how these maps represent information about sequences of natural, spectro-temporally rich sounds is sparse. We studied this question by conducting simultaneous extracellular recordings across IC depths in awake bats (Carollia perspicillata) that listened to sequences of natural communication and echolocation sounds. The hypothesis was that information about these two types of sound streams is represented at different IC depths since they exhibit large differences in spectral composition, i.e. echolocation covers the high frequency portion of the bat soundscape (> 45 kHz), while communication sounds are broadband and carry most power at low frequencies (20-25 kHz). Our results showed that mutual information between neuronal responses and acoustic stimuli, as well as response redundancy in pairs of neurons recorded simultaneously, increase exponentially with IC depth. The latter occurs regardless of the sound type presented to the bats (echolocation or communication). Taken together, our results indicate the existence of mutual information and redundancy maps at the midbrain level whose response cannot be predicted based on the frequency composition of natural sounds and classic neuronal tuning curves.
Frontal areas of the mammalian cortex are thought to be important for cognitive control and complex behaviour. These areas have been studied mostly in humans, non-human primates and rodents. In this article, we present a quantitative characterization of response properties of a frontal auditory area responsive to sound in the brain of Carollia perspicillata, the frontal auditory field (FAF). Bats are highly vocal animals, and they constitute an important experimental model for studying the auditory system. We combined electrophysiology experiments and computational simulations to compare the response properties of auditory neurons found in the bat FAF and auditory cortex (AC) to simple sounds (pure tones). Anatomical studies have shown that the latter provides feedforward inputs to the former. Our results show that bat FAF neurons are responsive to sounds, and however, when compared to AC neurons, they presented sparser, less precise spiking and longer-lasting responses. Based on the results of an integrate-and-fire neuronal model, we suggest that slow, subthreshold, synaptic dynamics can account for the activity pattern of neurons in the FAF. These properties reflect the general function of the frontal cortex and likely result from its connections with multiple brain regions, including cortico-cortical projections from the AC to the FAF.
Frontal areas of the mammalian cortex are thought to be important for cognitive control and complex behaviour. These areas have been studied mostly in humans, non-human primates and rodents. In this article, we present a quantitative characterization of response properties of a frontal auditory area responsive to sound in the bat brain, the frontal auditory field (FAF). Bats are highly vocal animals and they constitute an important experimental model for studying the auditory system. At present, little is known about neuronal sound processing in the bat FAF. We combined electrophysiology experiments and computational simulations to compare the response properties of auditory neurons found in the bat FAF and auditory cortex (AC) to simple sounds (pure tones). Anatomical studies have shown that the latter provide feedforward inputs to the former. Our results show that bat FAF neurons are responsive to sounds, however, when compared to AC neurons, they presented sparser, less precise spiking and longer-lasting responses. Based on the results of an integrate-and-fire neuronal model, we speculate that slow, low-threshold, synaptic dynamics could contribute to the changes in activity pattern that occur as information travels through cortico-cortical projections from the AC to the FAF.