Division of Neurobiology, Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA 94720-3200, USA
Address correspondence to Charles C. Lee, Department of Molecular and Cell Biology, Division of Neurobiology, Room 285 LSA, University of California at Berkeley, Berkeley, CA 94720-3200, USA. Email: chazwell{at}uclink4.berkeley.edu.
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Abstract |
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Key Words: maps thalamus tonotopy topography
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Introduction |
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In the cat auditory cortex, five areas have systematically organized maps of characteristic frequency (CF; tonotopic areas) (Imig and Reale, 1980; Rouiller et al., 1991
), i.e. the frequency at the lowest sound pressure level that evokes a response. Eight adjoining areas are non-tonotopic, containing auditory responsive neurons that are not systematically organized according to CF (Schreiner and Cynader, 1984
; Clarey and Irvine, 1990
; He et al., 1997
) and/or receiving thalamic input from auditory thalamic nuclei (Woolsey, 1960
; Imig and Reale, 1980
; Schreiner and Cynader, 1984
; Clarey and Irvine, 1990
; Rouiller et al., 1991
; He et al., 1997
) (Fig. 1A). Topographic projections from the medial geniculate body (MGB) (Morel and Imig, 1987
) and tonotopic cortical areas (Imig and Reale, 1980
) link frequency-matched loci in other tonotopic nuclei and areas (Lee et al., 2004a
). Non-tonotopic regions might be presumed a priori to have correspondingly less ordered, or even random, extrinsic projections that reflect this lack of tonotopic organization (Winer et al., 1977
). The same is true of limbic and association areas, whose broad responses may derive from the convergence of several modalities and systems that might obscure individual topographies (Bowman and Olson, 1988
; Shinonaga et al., 1994
; Clascá et al., 1997
). Alternatively, the lack of CF topography in non-tonotopic, limbic and association areas could also suggest that a metric besides frequency is mapped, perhaps requiring a topographic connectivity as ordered as that in the tonotopic regions. Distinguishing among these possible architectures has general implications for the physiology of the auditory forebrain and perhaps for its ontogeny.
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Materials and Methods |
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Operative procedures were conducted using sterile technique under veterinary supervision and adhered to the guidelines of the University of California at Berkeley animal care and use committee and those of the National Institutes of Health (Principles of Laboratory Animal Care, publication no. 85-23). We used standard procedures for anesthesia, surgery, physiology, and histology, as described in an earlier study (Lee et al., 2004a). Briefly, anatomical connectivity in 25 adult, female cats, weighing between 2.8 and 3.5 kg and free of middle ear disease, was studied using deposits of two retrograde tracers, much like the strategy employed in the monkey (Hackett et al., 1999
). Deposits guided by physiological mapping were made in four animals (Lee et al., 2004a
,b
), while 21 others were studied only anatomically (Fig. 2, Table 1). A nanoliter pump (World Precision Instruments, Sarasota, FL) was used to deliver a total volume of 55.2 nl (rate = 4.6 nl/30 s) at depths of 1500, 1000 and 500 µm beneath the pia surface of either of two separate tracers, cholera toxin beta subunit (CTß) (Luppi et al., 1990
) and cholera toxin beta subunit conjugated with gold (CTßG) (Llewellyn-Smith et al., 1990
) (List Biological Laboratories, Campbell, CA), into different sites in one or two areas (9 and 16 cases, respectively) (Fig. 1B). Retrogradely labeled cells from either tracer, as well as double-labeled neurons (Fig. 3D), were readily distinguished from one another (Lee et al., 2004a
). Multiple injections of each tracer, termed an injection set (23 injection penetrations/tracer/case), were often used due to limited tracer spread (
5001000 µm). In five cases, wheat-germ apo-horseradish peroxidase gold-conjugate (WAHG) (Basbaum and Menetrey, 1987
; Winer et al., 1996
) was used instead of CTßG; the results from the different tracers were indistinguishable.
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Data Analysis
Thalamic boundaries were drawn without knowledge of the labeling. Cytoarchitectonic subdivisions were established by reference to prior work (Winer, 1984b, 1985a
). For cortical areas, the SMI-32 immunostaining and the results from prior architectonic studies were available (Rose, 1949
; Winer, 1984a
,b
,c
, 1985b
; Winer and Prieto, 2001
). Deposit sites were reconstructed from adjacent sections. Each injection set (13 injections/tracer) was analyzed as a group by constructing a single polygon encircling all injections at their diffusion boundary, which was continuous between injections within the set. The area and centroid of the polygon enclosing the injection set was computed with the Neuroexplorer analysis software (MicroBrightField, Colchester, VT). Labeled neurons were charted using 1025x objectives on a microscope equipped with the computerized Neurolucida image-analysis system (MicroBrightField). Cortical labeling was reconstructed using the 3-D solids module in Neuroexplorer (MicroBrightField). Thalamic and cortical plot files were adjusted for shrinkage by 28% and imported to Canvas (Deneba Software Inc., Miami, FL), then aligned with surface and vascular landmarks to superimpose thalamic and cortical boundaries from cytoarchitectonic material. The number of neurons contributing to every projection was quantified, and the major projection in the thalamus and cortex was defined as the projection contributing maximally to the total extrinsic projection in each system, which constituted a unique cluster of neurons comprising >30% of thalamic input, >50% of commissural input, or >20% of corticocortical input. Measures of the topographic distribution of labeling used the Neuroexplorer analysis software.
The distance between the center of gravity of the major projections and that of the injection sites provided the scaling measure:
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Dispersion provided a measure of the spread of labeling, and was computed from a ratio of the area of the major projection and the area of the injection:
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A nearest neighbor algorithm computed clustering, which was defined as:
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Graphs of all distributions were produced with Excel (Microsoft Corp., Redmond, WA), and statistical analysis performed using Prism (GraphPad Software, San Diego, CA).
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Results |
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All Extrinsic Projections are Topographic
In every experiment, the pattern of thalamic and cortical retrograde labeling was clustered and topographic. This was apparent in thalamic sections following injections in both tonotopic (Fig. 4A) and non-tonotopic (Fig. 4BE) regions. Segregated clusters of thalamic (Fig. 4) and cortical (Fig. 5) cells project separately to each injection site, and a few neurons (<3%) were double labeled (Lee et al., 2004a). Input to the primary auditory cortex (AI) from the ventral division (V, Ov) of the medial geniculate body (MGB) was consistent with the characteristic frequency (CF) gradient in the MGB (Morel and Imig, 1987
) (Fig. 4A). The lateral-to-medial dispersion of MGB labeling after AI deposits was consistent with known projection patterns in both the thalamus and cortex (Morel and Imig, 1987
; Rouiller et al., 1991
; Lee et al., 2004a
). By comparison, after deposits in auditory regions devoid of CF maps, such as AII, Te, Ins, and AES, equally clustered and topographic projections arose from the MGB for each (Fig. 4BE). For instance, dorsal nucleus (D) projections to different domains in AII (Fig. 4B) had a range of clustering, convergence, and separation topographies (Fig. 1CE) indistinguishable from the values in tonotopic fields (Fig. 7). Minor labeling was found in V, which may result from encroachment of the injections into Ve (Fig. 4B). Dorsal caudal nucleus projections (DCa) followed similar metrics after injections in Te (Fig. 4C), as did labeling in the suprageniculate (Sgl, Sgm) and other dorsal division nuclei (deep dorsal nucleus: DD) after deposits in the insular (Ins) and anterior ectosylvian (AES) areas, respectively (Fig. 4D,E). Each of these areas is thought to be devoid of connectional topography (Clarey and Irvine, 1990
; Shinonaga et al., 1994
; Clascá et al., 1997
). Finally, deposits in the dorsolateral prefrontal cortex (DlP), a region involved in cognitive tasks and the evaluation of internal modes of action and unrelated to audition (Nauta, 1972
), labeled loci topographically in the ventral medial and midline thalamic nuclei (Fig. 4F: Vm, CM), suggesting that the projection patterns seen in auditory cortex may occur in non-sensory neocortex.
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Topographic Projections across Multiple Areas
Projections to different areas also were topographic and segregated. The major inputs from the thalamic or cortical sources arose in largely separate nuclei or areas. Interestingly, even two projections from the same nucleus or area were topographically segregated. For example, when frequency-matched (3 kHz) loci in two tonotopic regions are injected (Fig. 6A, circles), largely segregated thalamic (Fig. 6A) and cortical sources (Lee et al., 2004a) were labeled, even though such projections might be expected to commingle. This is consistent with the few (<3%) double-labeled neurons (Lee et al., 2004a
). Overlap regions, as in Ov (Fig. 6A), were highly clustered, but differed in the degree of this nuclear microsegregation. A further and comparable example of such nuclear segregation is seen after injections in two non-tonotopic regions, Ins and EPD (Fig. 6B). While the areas are unrelated physiologically and have independent functional affiliations (Bowman and Olson, 1988
; Clascá et al., 1997
), the labeling is still topographic and segregated in the thalamus (Fig. 6B) and cortex (Lee, 2004
).
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Three metrics were used to quantify topography. Clustering, dispersion, and separation indices were computed for all (thalamic, ipsilateral, and contralateral cortical) projections (see Methods) (Figs. 1CE and 7). For tonotopic, non-tonotopic, and limbic/association areas, the range of the descriptive measures of topography was statistically indistinguishable (P > 0.05, z-test) (Fig. 7AF), indicating that these different functional areas are ordered by the same metric. Comparison of injections within the same area that use either different tracers or number of deposits yields results that do not differ significantly from each other (P > 0.05, z-test), and illustrates the robustness of the results despite methodological variance of deposit size and placement.
Clustering is a measure of projection packing (Fig. 1E), and provides an index of the topographic continuity of the projection. This value was significantly lower (P < 0.05, z-test) in the thalamic projections (61 µm) compared with the cortical projections (96 µm) (Fig. 7AC), likely as a result of the larger cortical volume and different magnification factors, and it is reflected also by the lower variance of the cortical values (Fig. 7B,C).
The dispersion index is the ratio of the area of the projection zone to the area of the target (Fig. 1D), and it was also significantly lower (P < 0.05, z-test) in the thalamus (0.71) compared with the cortex (1.02) (Fig. 7AC). The thalamic value is slightly higher than expected considering its smaller size; however, the cortical value supports the notion that the ipsilateral and contralateral cortex projections originate from equivalent extrinsic areal domains.
Comparison of labeling separation with the deposit separation provides the scaling of projections in each system (Fig. 1C). Compared with cortical projections, thalamic projections were scaled by 33%, e.g. a 1 mm thalamic separation represents a 3 mm cortical separation (Fig. 7D,E). Commissural projections were the most highly clustered, arising from uniformly scaled, homotopic contralateral domains (Fig. 7F), while the thalamic projections exhibited the greatest topographic variability (Fig. 7D). Thus, all tonotopic and non-tonotopic areas and the dorsolateral prefrontal cortex have statistically indistinguishable topographic projections from extrinsic thalamic, ipsilateral, and contralateral cortical sources.
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Discussion |
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Constraints on Interpretation
This result may be influenced by methodological factors. We think this unlikely since we used sensitive tracers that reveal many more projection neurons than deposits of comparable size using older methods (Winguth and Winer, 1986; Matsubara and Phillips, 1988
). While transected fibers may contribute slightly to this result (Luppi et al., 1990
), the small volume of the deposits (
1 mm3) and their confinement to one architectonic area and to the cortical gray matter would limit this. If tracer had spread appreciably, we should expect to see a degradation of the topography, which was not the case. Nor do multiple injections appear to confound the results. If the observed topography does represent such degradation, then the actual precision of these projections would be remarkable.
We recognize, however, that each metric has limited utility, and the robustness of the current results may yield to finer discriminative measures that would be appropriate in the case of smaller deposits or injections confined to a physiological subregion of cortex (Read et al., 2001). The thrust of this study is the question whether any single metric could capture the connectivity of tonotopic and non-tonotopic areas, and to assess this across many areas, nuclei, and deposits on a global basis. The internal organization of subsets of these connections is another matter and beyond the scope of the present study.
The metrics employed in this study were chosen for both their conceptual power and computational simplicity. Each measure can be viewed as sensitive to different anatomical scales of topography. At the finest scale, clustering provides a measure of the topographic continuity of the projection ensemble; while at an intermediate scale, dispersion establishes the convergent relation between projection source and target. At the largest scale, separation measures the organization of the topographic projections in relation to each other across the cortex. Thus, each measure taps independent aspects of the topographic organization, as evinced by the variance among the three metrics (Fig. 7), and each thus provides an orthogonal basis for comparing the topography in each system.
An Isotropic Connectional Principle
This study reveals an isotropic relation in auditory neocortex and thalamus that includes all areas and nuclear subdivisions investigated, respectively. It thus departs from other forms of local organization, such as ocular dominance, which is limited to certain visual areas (LeVay et al., 1975), or somatic sensory barrels and their representations, which are restricted to specific and singular functional subregions of the trigeminal system (Ma, 1993
), ventrobasal complex (Land et al., 1995
) and somatic sensory cortex (Woolsey and Van der Loos, 1970
). The uniformity and homogeneous distribution of this connectional topography suggests a common principle not limited to specific sensory processing.
Perhaps this topographic principle is a residue of the developmental plan for constructing the forebrain, specifying the sequential and temporal emergence of specific neuronal populations to complete their ontogenetic assignment (Molnár and Blakemore, 1995). The genetic encoding of this topography could ensure that the appropriate thalamic axons are matched with their correct targets, perhaps operating through a general set of chemically specified guidance cues (Grove and Fukuchi-Shimogori, 2003
), though such specificity seems absent in some culture regimes (Molnár and Blakemore, 1991
).
Such a topographic metric could coordinate the operations of physiologically distinct thalamic nuclei and cortical areas along a common, normalized scale. Interestingly, such scalar relations would supervene across different tonotopic magnification factors (Schreiner, 1992) as in AI and AAF, which have unique cochleotopic representations (Lee et al., 2004a
) and different magnification factors (Imaizumi et al., 2004
). Topographic uniformity could thus enable functionally non-equivalent fields to temporally synchronize matched inputs. Such coordinated activation could affect aspects of cortical function ranging from temporal discharge synchrony (Dickson and Gerstein, 1974
) to the conditions enabling binding (Treisman, 1999
), which presumably require such a topographic connectivity for inter-areal signal propagation.
Multiple physiological representations could be supported by these topographic connections. In AI, the topographic (present results) and tonotopic (Merzenich et al., 1975) frames of reference are aligned, but coexisting representations of binaurality (Middlebrooks et al., 1980
) and sharpness of tuning (Read et al., 2001
) are interleaved (Ehret, 1997
; Read et al., 2001
). By comparison, AII contains only a coarse gradient of frequency and binaural segregation appears absent (Schreiner and Cynader, 1984
), with similar patterns of limited local segregation prevailing in other cortical subdivisions (Winer, 1992
). This suggests that the ontogenetic assembly of AI, where topography is mapped more fully, may be simpler than that in AII and related fields, where less regular physiologic arrangements are superimposed on a topographic scaffold as ordered as that in AI but whose tonotopy is weaker. Alternatively, the physiologic metrics in areas such as AII may be unrelated to the tonotopic framework, and may instead be derived for computed parameters, as in the midbrain auditory space maps (Masterton, 1992
).
Prior connectional studies of auditory cortex have emphasized that thalamic (Winer et al., 1977), commissural (Code and Winer, 1985
) and corticocortical (Winguth and Winer, 1986
) inputs each have topographic and non-topographic components. Such conclusions were reached without recourse to the simple but robust connectional metrics available in the present study, and are therefore of limited value with regard to topography and precision of projection.
Historically, primary sensory neocortex has been described as having a modular organization (Szentágothai, 1975) and a complementary architectonic homogeneity (Bok, 1959
) and isodensity profile, with a few exceptions (Rockel et al., 1980
). The topographic arrangement reported here extends this to the scale of global connections and links all extrinsic projection systems to a singular, simple principle. It remains to be seen how far this isotropic principle extends to other sites, systems, and modalities.
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Acknowledgments |
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References |
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![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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Bok ST (1959) Histonomy of the cerebral cortex. Amsterdam: Elsevier.
Bowman EM, Olson CR (1988) Visual and auditory association areas of the cat's posterior ectosylvian gyrus: thalamic afferents. J Comp Neurol 272:1529.[CrossRef][ISI][Medline]
Cavada C, Reinoso-Suárez F (1985) Topographical organization of the cortical afferent connections of the prefrontal cortex in the cat. J Comp Neurol 242:293324.[CrossRef][ISI][Medline]
Clarey JC, Irvine DRF (1990) The anterior ectosylvian sulcal auditory field in the cat. I. An electrophysiological study of its relation to surrounding auditory cortical fields. J Comp Neurol 301:289303.[CrossRef][ISI][Medline]
Clascá F, Llamas A, Reinoso-Suárez F (1997) Insular cortex and neighboring fields in the cat: a redefinition based on cortical microarchitecture and connections with the thalamus. J Comp Neurol 384:456482.[CrossRef][ISI][Medline]
Code RA, Winer JA (1985) Commissural neurons in layer III of cat primary auditory cortex (AI): pyramidal and non-pyramidal cell input. J Comp Neurol 242:485510.[CrossRef][ISI][Medline]
Dickson JW, Gerstein GL (1974) Interactions between neurons in auditory cortex of the cat. J Neurophysiol 37:12391261.
Ehret G (1997) The auditory cortex. J Comp Physiol A 181:547557.[ISI][Medline]
Grove EA, Fukuchi-Shimogori T (2003) Generating the cerebral cortical area map. Annu Rev Neurosci 26:355380.[CrossRef][ISI][Medline]
Hackett TA, Stepniewska I, Kaas JH (1999) Callosal connections of the parabelt auditory cortex in macaque monkeys. Eur J Neurosci 11:856866.[CrossRef][ISI][Medline]
He J, Hashikawa T, Ojima H, Kinouchi Y (1997) Temporal integration and duration tuning in the dorsal zone of cat auditory cortex. J Neurosci 17:26152625.
Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol (Lond) 160:106154.[ISI][Medline]
Imaizumi K, Priebe NJ, Crum PAC, Bedenbaugh PH, Cheung SW, Schreiner CE (2004) Modular functional organization of cat anterior auditory field. J Neurophysiol 92:444457.
Imig TJ, Reale RA (1980) Patterns of cortico-cortical connections related to tonotopic maps in cat auditory cortex. J Comp Neurol 192:293332.[CrossRef][ISI][Medline]
Kaas JH (1982) The segregation of function in the nervous system: why do sensory systems have so many subdivisions? In: Contributions to sensory physiology (Neff WD, ed.), pp. 201240. New York: Academic Press.
Kaas JH (1997) Topographic maps are fundamental to sensory processing. Brain Res Bull 44:107112.[CrossRef][ISI][Medline]
Kaas JH, Nelson RJ, Sur M, Lin C-S, Merzenich MM (1979) Multiple representations of the body within the primary somatosensory cortex of primates. Science 204:521523.[ISI][Medline]
Land PW, Buffer SA Jr, Yaskosky JD (1995) Barreloids in adult rat thalamus: three-dimensional architecture and relationship to somatosensory cortical barrels. J Comp Neurol 355:573588.[CrossRef][ISI][Medline]
Lee CC (2004) Structure of the cat auditory cortex. PhD Dissertation, University of California at Berkeley.
Lee CC, Winer JA (2002) Commissural connections in cat auditory cortex. Proc Soc Neurosci 28:261.
Lee CC, Winer JA (2003) Topographic projections in cat auditory cortex. Proc Soc Neurosci 29:592.
Lee CC, Imaizumi K, Schreiner CE, Winer JA (2004a) Concurrent tonotopic processing streams in auditory cortex. Cereb Cortex 14:441451.
Lee CC, Schreiner CE, Imaizumi K, Winer JA (2004b) Tonotopic and heterotopic projection systems in physiologically defined auditory cortex. Neuroscience 128:871887.[CrossRef][ISI][Medline]
LeVay S, Hubel DH, Wiesel TN (1975) The pattern of ocular dominance columns in macaque visual cortex revealed by a reduced silver stain. J Comp Neurol 159:559576.[CrossRef][ISI][Medline]
Llewellyn-Smith IJ, Minson JB, Wright AP, Hodgson AJ (1990) Cholera toxin B-gold, a retrograde tracer that can be used in light and electron microscopic immunocytochemical studies. J Comp Neurol 294:179191.[CrossRef][ISI][Medline]
Luppi P-H, Fort P, Jouvet M (1990) Iontophoretic application of unconjugated cholera toxin B subunit (CTb) combined with immunohistochemistry of neurochemical substances: a method for transmitter identification of retrogradely labeled neurons. Brain Res 534:209224.[CrossRef][ISI][Medline]
Ma PM (1993) Barrelettes-architectonic vibrissal representations in the brainstem trigeminal complex of the mouse. II. Normal postnatal development. J Comp Neurol 327:376397.[CrossRef][ISI][Medline]
Malonek D, Tootell RBH, Grinvald A (1994) Optical imaging reveals the functional architecture of neurons processing shape and motion in owl monkey area MT. Proc R Soc Lond B Biol Sci 258:109119.[ISI][Medline]
Masterton RB (1992) Role of the central auditory system in hearing: the new direction. Trends Neurosci 15:280285.[CrossRef][ISI][Medline]
Matsubara JA, Phillips DP (1988) Intracortical connections and their physiological correlates in the primary auditory cortex (AI) of the cat. J Comp Neurol 268:3848.[CrossRef][ISI][Medline]
Mellot JG, van Der Gucht E, Lee CC, Larue DT, Winer JA, Lomber SG (2005) Subdividing cat primary and non-primary auditory areas in the cerebrum with neurofilament proteins expressing SMI-32. Assn Res Otolaryngol Abstr 28:994.
Merzenich MM, Knight PL, Roth GL (1975) Representation of cochlea within primary auditory cortex in the cat. J Neurophysiol 38:231249.
Middlebrooks JC, Dykes RW, Merzenich MM (1980) Binaural response-specific bands in primary auditory cortex (AI) of the cat: topographic organization orthogonal to isofrequency contours. Brain Res 181:3148.[CrossRef][ISI][Medline]
Molnár Z, Blakemore C (1991) Lack of regional specificity for connections formed between thalamus and cortex in coculture. Nature 351:475477.[CrossRef][ISI][Medline]
Molnár Z, Blakemore C (1995) How do thalamic axons find their way to the cortex? Cereb Cortex 18:389397.
Morel A, Imig TJ (1987) Thalamic projections to fields A, AI, P, and VP in the cat auditory cortex. J Comp Neurol 265:119144.[CrossRef][ISI][Medline]
Nauta WJH (1972) Neural associations of the frontal cortex. Acta Neurobiol Exp (Warsz) 32:125140.[Medline]
Obermeyer K, Sejnowski TJ (2001) Self-organizing map formation: foundations of neural computation. London: MIT Press.
Peters A, Jones EG (eds) (1985) Cerebral cortex. Vol. 4. Association and auditory cortices. New York: Plenum Press.
Read HL, Winer JA, Schreiner CE (2001) Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex. Proc Natl Acad Sci USA 98:80428047.
Rockel AJ, Hiorns RW, Powell TPS (1980) The basic uniformity in structure of the neocortex. Brain 103:221244.[ISI][Medline]
Rose JE (1949) The cellular structure of the auditory region of the cat. J Comp Neurol 91:409440.[CrossRef][ISI][Medline]
Rouiller EM, Simm GM, Villa AEP, de Ribaupierre Y, de Ribaupierre F (1991) Auditory corticocortical interconnections in the cat: evidence for parallel and hierarchical arrangement of the auditory cortical areas. Exp Brain Res 86:483505.[ISI][Medline]
Schreiner CE (1992) Functional organization of the auditory cortex: maps and mechanisms. Curr Opin Neurobiol 2:516521.[CrossRef][Medline]
Schreiner CE, Cynader MS (1984) Basic functional organization of second auditory cortical field (AII) of the cat. J Neurophysiol 51:12841305.
Shinonaga Y, Takada M, Mizuno N (1994) Direct projections from the non-laminated divisions of the medial geniculate nucleus to the temporal polar cortex and amygdala in the cat. J Comp Neurol 340:405426.[CrossRef][ISI][Medline]
Sternberger LA, Sternberger NH (1983) Monoclonal antibodies that distinguish phosphorylated and nonphosphorylated forms of filament in situ. Proc Natl Acad Sci USA 80:61266130.
Szentágothai J (1975) The module-concept in cerebral cortex architecture. Brain Res 95:475496.[CrossRef][ISI][Medline]
Treisman A (1999) Solutions to the binding problem: progress through controversy and convergence. Neuron 24:105110.[CrossRef][ISI][Medline]
Tusa RJ, Palmer LA, Rosenquist AC (1978) The retinotopic organization of area 17 (striate cortex) in the cat. J Comp Neurol 177:213236.[CrossRef][ISI][Medline]
Tusa RJ, Rosenquist AC, Palmer LA (1979) Retinotopic organization of areas 18 and 19 in the cat. J Comp Neurol 185:657678.[CrossRef][ISI][Medline]
Winer JA (1984a) Anatomy of layer IV in cat primary auditory cortex (AI). J Comp Neurol 224:535567.[CrossRef][ISI][Medline]
Winer JA (1984b) Identification and structure of neurons in the medial geniculate body projecting to primary auditory cortex (AI) in the cat. Neuroscience 13:395413.[CrossRef][ISI][Medline]
Winer JA (1984c) The non-pyramidal neurons in layer III of cat primary auditory cortex (AI). J Comp Neurol 229:512530.[CrossRef][ISI][Medline]
Winer JA (1985a) The medial geniculate body of the cat. Adv Anat Embryol Cell Biol 86:198.[ISI][Medline]
Winer JA (1985b) Structure of layer II in cat primary auditory cortex (AI). J Comp Neurol 238:1037.[CrossRef][ISI][Medline]
Winer JA (1992) The functional architecture of the medial geniculate body and the primary auditory cortex. In: Springer handbook of auditory research. Vol. 1. The mammalian auditory pathway: neuroanatomy (Webster DB, Popper AN, Fay RR, eds), pp. 222409. New York: Springer-Verlag.
Winer JA, Prieto JJ (2001) Layer V in cat primary auditory cortex (AI): cellular architecture and identification of projection neurons. J Comp Neurol 434:379412.[CrossRef][ISI][Medline]
Winer JA, Diamond IT, Raczkowski D (1977) Subdivisions of the auditory cortex of the cat: the retrograde transport of horseradish peroxidase to the medial geniculate body and posterior thalamic nuclei. J Comp Neurol 176:387418.[CrossRef][ISI][Medline]
Winer JA, Saint Marie RL, Larue DT, Oliver DL (1996) GABAergic feedforward projections from the inferior colliculus to the medial geniculate body. Proc Natl Acad Sci USA 93:80058010.
Winguth SD, Winer JA (1986) Corticocortical connections of cat primary auditory cortex (AI): laminar organization and identification of supragranular neurons projecting to area AII. J Comp Neurol 248:3656.[CrossRef][ISI][Medline]
Woolsey CN (1960) Organization of cortical auditory system: a review and synthesis. In: Neural mechanisms of the auditory and vestibular systems (Rasmussen GL, Windle WF, eds), pp. 165180. Springfield, IL: Charles C Thomas.
Woolsey TA, Van der Loos H (1970) The structural organization of layer IV in the somatosensory region (S I) of mouse cerebral cortex. Brain Res 17:205242.[CrossRef][ISI][Medline]
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