Formation and disruption of tonotopy in a large-scale model of the auditory cortex

Neurod1 Is Essential for the Primary Tonotopic Organization and Related Auditory Information Processing in the Midbrain

Hearing depends on extracting frequency, intensity, and temporal properties from sound to generate an auditory map for acoustical signal processing. How physiology intersects with molecular specification to fine tune the developing properties of the auditory system that enable these aspects remains unclear. We made a novel conditional deletion model that eliminates the transcription factor NEUROD1 exclusively in the ear. These mice (both sexes) develop a truncated frequency range with no neuroanatomically recognizable mapping of spiral ganglion neurons onto distinct locations in the cochlea nor a cochleotopic map presenting topographically discrete projections to the cochlear nuclei. The disorganized primary cochleotopic map alters tuning properties of the inferior colliculus units, which display abnormal frequency, intensity, and temporal sound coding. At the behavioral level, animals show alterations in the acoustic startle response, consistent with altered neuroanatomical and physiological properties. We demonstrate that absence of the primary afferent topology during embryonic development leads to dysfunctional tonotopy of the auditory system. Such effects have never been investigated in other sensory systems because of the lack of comparable single gene mutation models.SIGNIFICANCE STATEMENT All sensory systems form a topographical map of neuronal projections from peripheral sensory organs to the brain. Neuronal projections in the auditory pathway are cochleotopically organized, providing a tonotopic map of sound frequencies. Primary sensory maps typically arise by molecular cues, requiring physiological refinements. Past work has demonstrated physiologic plasticity in many senses without ever molecularly undoing the specific mapping of an entire primary sensory projection. We genetically manipulated primary auditory neurons to generate a scrambled cochleotopic projection. Eliminating tonotopic representation to auditory nuclei demonstrates the inability of physiological processes to restore a tonotopic presentation of sound in the midbrain. Our data provide the first insights into the limits of physiology-mediated brainstem plasticity during the development of the auditory system.

A Computational Model of Thalamocortical Dysrhythmia in People With Tinnitus

Tinnitus is a problem that affects a diverse range of people. One common trait amongst people with tinnitus is the presence of hearing loss, which is apparent in over 90% of the cohort. It is postulated that the remainder of people with tinnitus have hidden hearing loss in the form of cochlear synaptopathy. The loss of hearing sensation is thought to cause a reduction in the bottom-up excitatory signals of the auditory pathway leading to a change in the frequency of thalamocortical oscillations known as thalamocortical dysrhythmia (TCD). The downward shift in oscillatory behavior, characteristic of TCD, has been recorded experimentally but the underlying mechanisms responsible for TCD in tinnitus subjects cannot be directly observed. This paper investigates these underlying mechanisms by creating a biologically faithful model of the auditory periphery and thalamocortical network, called the central auditory processing (CAP) model. The proposed model replicates tinnitus related activity in the presence of hearing loss and hidden hearing loss in the form of cochlear synaptopathy. The results of this paper show that, both the bottom-up and top-down changes are required in the auditory system for tinnitus related hyperactivity to coexist with TCD, contrary to the theoretical model for TCD. The CAP model provides a novel modeling approach to account for tinnitus related activity with and without hearing loss. Moreover, the results provide additional clarity to the understanding of TCD and tinnitus and provide direction for future approaches to treating tinnitus.

Controllability Analysis of the Neural Mass Model with Dynamic Parameters

The development of control technology for the brain is of potential significance to the prevention and treatment of neuropsychiatric disorders and the improvement of humans' mental health. A controllability analysis of the brain is necessary to ensure the feasibility of the brain control. In this letter, we investigate the influences of dynamical parameters on the controllability in the neural mass model by using controllability indices as quantitative indicators. The indices are obtained by computing Lie brackets and condition numbers of the system model. We show how controllability changes with important parameters of our dynamical (neuronal) model. Our results suggest that the underlying dynamical parameters have certain ranges with better controllability. We hope it can play potential roles in therapy for brain nervous disorder disease.