Auditory cortex mapmaking: principles, projections, and plasticity

Abstract

Maps of sensory receptor epithelia and computed features of the sensory environment are common elements of auditory, visual, and somatic sensory representations from the periphery to the cerebral cortex. Maps enhance the understanding of normal neural organization and its modification by pathology and experience. They underlie the derivation of the computational principles that govern sensory processing and the generation of perception. Despite their intuitive explanatory power, the functions of and rules for organizing maps and their plasticity are not well understood. Some puzzles of auditory cortical map organization are that few complete receptor maps are available and that even fewer computational maps are known beyond primary cortical areas. Neuroanatomical evidence suggests equally organized connectional patterns throughout the cortical hierarchy that might underlie map stability. Here, we consider the implications of auditory cortical map organization and its plasticity and evaluate the complementary role of maps in representation and computation from an auditory perspective.

Fig. 1. Auditory Cortical Areas in Two Mammalian Species

(A) Cat auditory cortex has at least thirteen areas, of which five are tonotopic (black), three are non-tonotopic (dark gray), and five are non-tonotopic, multimodal/or and limbic-related (light gray). A color gradient indicates the frequency map along the basilar membrane (depicted beneath the cochlea) and its replication in the primary auditory cortex (AI). Arrows, indicate low-to-high frequency gradients in the five tonotopic fields. (B) In the rhesus monkey, the superior temporal gyrus contains multiple tonotopic fields divided into core (R, AI, etc.), belt (AL, ML, etc.) and less well-defined parabelt regions along the superior temporal plane. Redrawn from (Hackett et al., 2001; Rauschecker and Tian, 2000). Abbreviations for all figures: AAF, anterior auditory field; AES, anterior ectosylvian area; aes, anterior ectosylvian sulcus; AI, primary auditory cortex; AII, secondary auditory area; AL, anterolateral belt; CL, caudolateral belt; CM, caudomedial auditory belt; DZ, dorsal auditory zone; ED; posterior ectosylvian gyrus, dorsal part; EI; posterior ectosylvian gyrus, intermediate part; EV, posterior ectosylvian gyrus, ventral part; In, insular cortex; pes, posterior ectosylvian sulcus; LS, lateral sulcus; P, posterior auditory field; R, rostral auditory field; RM, rostromedial region; RT, rostrotemporal area; RTL, rostral temporal cortex, lateral area; RTM, medial rostrotemporal auditory belt; STG, superior temporal gyrus; sss, suprasylvian sulcus; STS, superior temporal sulcus; Te, temporal cortex; Ve, ventral auditory area; VIIIn, eight nerve; VP, ventroposterior area; wm, white matter.

Fig. 2. Multiple Functional Topographies Coexist in Primary Auditory Cortex (AI)

(A) A lateral view of cat auditory cortex shows a color-coded tonotopic gradient of AI for near-threshold tones. (B) The same region of AI is replotted combining frequency gradient (color coded as in A) with a pseudo-three-dimensional depiction of the frequency range encompassed by each cortical point when stimulated with tones 40 dB above response threshold. The peak surface elevations correspond to response ranges of 5 octaves, nearly covering the full color-coded frequency range, thus, significantly degrading the cochleotopic gradient. (C) Functional subregions of the isofrequency domain in cat AI. Dorsal AI is dominated by broadly tuned, aurality-specific neurons, often with multipeaked tuning curves. The central region contains sharply-tuned neurons of different aurality, and the ventral region has a mix of sharply and broadly tuned neurons with a large local scatter of center frequencies (CFs) for both binaural interaction types. Directional FM sweep preferences for high and low CFs, gray arrows (Winer and Schreiner, 2005).

Figure 3. All Extrinsic Projections to Auditory Cortex Are Ordered Equally

(A) Schematic depiction of typical patterns of corticocortical retrograde connectivity in cat AI. The light gray-to-dark gray polygons correspond to frequency polygons across AI as a Voronoi-Direchlet tessellation; the border with the anterior auditory field (AAF) is marked (dashed white line) and shows a frequency gradient reversal. Two deposits of different retrograde tracers were placed in AI and label homotopic (frequency matched) and heterotopic (mismatched) AAF zones. (B) For topographical analysis, auditory cortex dispersion and clustering/convergence indices were computed. The dispersion index is the ratio of the area of labeling to the area of the injection (circles in AI in panel A). Clustering measures the average distance between neighboring projecting neurons. The measures are similar for all three types of cortical areas. Modified from Lee and Winer (2005). (C) Separation graphs depict projection scaling in the corticocortical pathways. Each dot represents all neurons labeled in one dual injection experiment. The regression line slopes shows that the scaling of the cortical projections is independent of the cortical injection locus. Modified from Lee and Winer (2005).