Sparse Coding in Temporal Association Cortex Improves Complex Sound Discriminability

Abstract

The mouse auditory cortex is comprised of several auditory fields spanning the dorsoventral axis of the temporal lobe. The ventral most auditory field is the temporal association cortex (TeA), which remains largely unstudied. Using Neuropixels probes, we simultaneously recorded from primary auditory cortex (AUDp), secondary auditory cortex (AUDv), and TeA, characterizing neuronal responses to pure tones and frequency modulated (FM) sweeps in awake head-restrained female mice. As compared with AUDp and AUDv, single-unit (SU) responses to pure tones in TeA were sparser, delayed, and prolonged. Responses to FMs were also sparser. Population analysis showed that the sparser responses in TeA render it less sensitive to pure tones, yet more sensitive to FMs. When characterizing responses to pure tones under anesthesia, the distinct signature of TeA was changed considerably as compared with that in awake mice, implying that responses in TeA are strongly modulated by non-feedforward connections. Together, these findings provide a basic electrophysiological description of TeA as an integral part of sound processing along the cortical hierarchy.

Surround suppression in mouse auditory cortex underlies auditory edge detection

“…That is, the model FBRA is the one with the highest correlation between model and neuronal FBRAs. The μ values, which are determined by our electrode penetration in relation to the tonotopic axis, were centered at low frequencies (10.5 ± 9.4 kHz; mean±SD), consistent with previous Neuropixels recording experiments from our lab [43]. The mean w values were 0.26 ± 0.25 octaves, which are on the order of magnitude of common measures of bandwidth in awake mouse ACx [40] (although w here is not precisely bandwidth; see Methods).…”

“…In each mouse, we performed one or two consecutive probe penetrations. Probe trajectories were reconstructed from consecutive coronal slices as detailed in earlier work [ 43 , 62 ] and using an open source software ([ 75 ]; Fig 1D ). Following the reconstruction, probe channels were annotated to the corresponding brain regions they were recording from (see Table 1 ).…”

“Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex”

“…where 𝑟 ( is the average response of a neuron to the ith sound pressure level at a given laser activation calculated over its optimal time window minus the neuron's response to laser activation and silence, and 𝑛 is the number of sound pressure levels (response in silence excluded). Similar to how this measure is computed with the firing rate of excited neurons (Rolls and Tovee, 1995;Vinje and Gallant, 2000;Olsen and Wilson, 2008;Feigin et al, 2021), we adapted the sparseness measure to fluorescence data by setting any values of 𝑟 ( < 0 to zero before calculating the sparseness, and by calculating this measure only for neurons with at least one positive 𝑟 ( , for which the sparseness is well-defined (at least one positive 𝑟 𝑖 ). A sparseness value of 0% indicates that a neuron's responses to all sound pressure levels are equal, and a sparseness value of 100% indicates that a neuron only responds to one sound pressure level.…”

Maternal microbes and early brain development in mouse

“…Brain volume change is a powerful correlate of neurodevelopmental and neurocognitive outcomes of individuals (47,48), and MRI is a non-invasive method that allows for the complete examination of brain structure changes in a single experimental run. We observed broad structural volume alteration specific to the somatosensory in GF mice, critical for general and higher-order sensory processing and integration (49–53), compared to their age-matched SPF counterparts (Figure 1B, 3B, and Supplementary Figure 1). This is consistent with previous reports detailing defects in sensory processing in neuropsychiatric conditions associated with a disturbed gut microbiome (13,54,55).…”