Lemniscal Corticothalamic Feedback in Auditory Scene Analysis

Abstract

Sound information is transmitted from the ear to central auditory stations of the brain via several nuclei. In addition to these ascending pathways there exist descending projections that can influence the information processing at each of these nuclei. A major descending pathway in the auditory system is the feedback projection from layer VI of the primary auditory cortex (A1) to the ventral division of medial geniculate body (MGBv) in the thalamus. The corticothalamic axons have small glutamatergic terminals that can modulate thalamic processing and thalamocortical information transmission. Corticothalamic neurons also provide input to GABAergic neurons of the thalamic reticular nucleus (TRN) that receives collaterals from the ascending thalamic axons. The balance of corticothalamic and TRN inputs has been shown to refine frequency tuning, firing patterns, and gating of MGBv neurons. Therefore, the thalamus is not merely a relay stage in the chain of auditory nuclei but does participate in complex aspects of sound processing that include top-down modulations. In this review, we aim (i) to examine how lemniscal corticothalamic feedback modulates responses in MGBv neurons, and (ii) to explore how the feedback contributes to auditory scene analysis, particularly on frequency and harmonic perception. Finally, we will discuss potential implications of the role of corticothalamic feedback in music and speech perception, where precise spectral and temporal processing is essential.

Corticothalamic projections deliver enhanced responses to medial geniculate body as a function of the temporal reliability of the stimulus

“…2016; Pichora‐Fuller et al . 2017; Homma & Bajo Lorenzana, 2021). Peripheral deficits only partially account for the age‐related loss of speech understanding, temporal discrimination and the ability to attend to acoustic stimuli.…”

“…2012; Mihai et al . 2019; Homma & Bajo Lorenzana, 2021; Tabas & von Kriegstein, 2021). The MGB receives top‐down/corticofugal information from extensive descending corticothalamic (CT) projections (Rouiller & Welker, 1991; Winer et al .…”

“…Speech intelligibility can be maintained in noisy backgrounds and in the aged auditory system by increased use of linguistic/contextual redundancies and predictability to substitute for sensory deficits (Warren, 1970;Wingfield, 1975;Peelle & Wingfield, 2016;Pichora-Fuller et al 2016;. For young adults in cluttered acoustic environments and older individuals affected by age-related hearing loss (presbycusis), higher-order/cortical resources are brought into play to help disambiguate acoustic signals (Shinn-Cunningham & Wang, 2008;Davis et al 2011;Obleser, 2014;Başkent et al 2016;Vaden et al 2016;Pichora-Fuller et al 2017;Homma & Bajo Lorenzana, 2021). Peripheral deficits only partially account for the age-related loss of speech understanding, temporal discrimination and the ability to attend to acoustic stimuli.…”

“…The auditory thalamus is a key subcortical structure in auditory processing. Sensory systems show attention/task/context-dependent changes in thalamic activity, probably reflecting increasingly engaged corticofugal circuits (von Kriegstein et al 2008;Saalmann & Kastner, 2011;Diaz et al 2012;Mihai et al 2019;Homma & Bajo Lorenzana, 2021;Tabas & von Kriegstein, 2021). The MGB receives top-down/corticofugal information from extensive descending corticothalamic (CT) projections (Rouiller & Welker, 1991;Winer et al 2001;He, 2003;Bartlett, 2013;Guo et al 2017;Parras et al 2017).…”

Deep Ultraviolet Light Stimulated Synaptic Transistors Based on Poly(3-hexylthiophene) Ultrathin Films

“…In the era of the Internet of Things and Big Data, the storage and processing of massive amounts of information are evolving as an imminent problem that has to be addressed as soon as possible. , Although computer systems based on the traditional “von Neumann architecture” can typically handle such a large amount of data, its separate information storage and processing modules gradually display significant disadvantages in today’s society and thus are no longer able to meet the needs of the users. , Along these lines, the emergence of artificial neural networks has emerged as a quite promising alternative solution. As the most sophisticated organ in our body, the brain receives information from the vast sensory network every day and controls the body’s reactions, ranging from simple pronunciation, walking, and even more difficult learning and thinking procedures . All of the above-mentioned processes are exceptionally coordinated and controlled by the brain .…”