http://www.glue.umd.edu/~carr/Hearing/lecture9.html
Catherine Carr in her lectures refers to the work of JH Casseday and E Covey:
LECTURE 9 Midbrain 4/6/99
Lecture 9 will conclude the neurobiological survey of the auditory system. The field has been dominated by the bottom-up approach and thus there is less known about auditory processing in cortex than about processing at other levels.
Reading
Clarey, J.C., Barone, P. and Imig, T.J. (1992) Physiology of thalamus and cortex.. In The mammalian auditory pathway: Neurophysiology, Eds., Springer-Verlag, New York, pp. 232-334.
H. L. Hawkins and T. A. McMullen (1997) Auditory Computation: an Overview, In: Auditory Computation H.L. Hawkins and T.A. McMullen, A.N. Popper and R.R. Fay (eds.)
*Lyon, R. and Shamma, S. (1996) Auditory representations of timbre and pitch. In Auditory computation, H.L. Hawkins, T.A. McMullen, A.N. Popper, R.R. Fay, Eds., Springer-Verlag, New York, pp. 221-270
N. Kowalski and D.A. Depireux and S.A. Shamma, Analysis of dynamic spectra in ferret primary auditory cortex. {I &II} Characteristics of single-unit responses to moving ripple spectra. J.Neurophys.76: 3503--3523 and 3524--3534 (1996)
Outline
I. Auditory Midbrain – Inferior colliculus
Cellular Organization and Physiology of Mammalian IC
IC projections to motor systems
See figure of tectofugal pathways; extensive IC projection into register with visual map in SC. Drives orientation to stimuli (see Covey and Casseday below)
Current ideas about mammalian IC function from Cassaday and Covey (modified summary)
A general statement of the function of the inferior colliculus is lacking, even after more than three decades of electrophysiological investigation. A neuroethological theory is proposed that accounts for a large and diverse body of evidence. Although aimed at characterizing the inferior colliculus in mammals, the theory also applies generally to the auditory midbrain in vertebrates. The theory has two hypotheses:
Expressed in neuroethological terms, at least some neurons in the inferior colliculus are tuned to sign-stimuli (behaviorally relevant stimuli that trigger species specific behavior), and the processing of these sign stimuli triggers fixed action patterns for hunting, escape or vocal communication. The resulting temporal transformation adjusts the pace of sensory input to the pace of behavior. Evidence for the theory comes from anatomical, neurophysiological and behavioral studies and includes:
The theory has the following implications. Neurons in the inferior colliculus are filters for sounds that require immediate action, such as certain sounds made by prey, predators or conspecifics. Neural processing in the inferior colliculus is species specific, resulting in filtering for these kinds of sounds. Specific action patterns should be correlated with the activity of neurons in the inferior colliculus. Motor activates may modify neural processing in inferior colliculus neurons. The rate at which information is transmitted to the thalamus is regulated by the inferior colliculus. Lets discuss this.
II Introduction to thalamus and cortex
Major conclusions about auditory forebrain in vertebrates
Hair cells è Primary è Olivary è midbrain è thalamus è Cortical/pallial
Hypothalamus subcortical/subpallial
Summary of auditory forebrain connections in vertebrates
See class handout
III Auditory thalamus
Structure and function of Medial Geniculate
Divided into 3 subdivisions, M, V & D.
Ventral receives major ascending input from ICC. Contains sharply tuned cells like in IC, tonotopically organized although the organization is not that simple — e.g. contains a concentric component with low frequencies in the center.
Dorsal division cells unresponsive to tone or noise, when do respond, latencies are long, all consistent with major projection back from peri-rhinal cortex
Medial like dorsal, little evidence of tonotopy.
Physiology
Functional arguments less clear. Non-monotonic responses more common than monotonic (ie like CN). More in ventral than medial
In bat, find delay tuned neurons in both medial and dorsal divisions (pulse-echo facilitation). In this example, assemble new code for delay tuned neurons — combination sensitive neurons, facilitation from cortex.
Fear Conditioning (from article about LeDoux lab)
Paradigm — use rats, pairing foot shock with a tone. Pair the tone and the shock in memory, thereby making the tone a harbinger of threat. The tone alone then triggers a fear response: It activates the autonomic nervous system, which controls heart rate and blood pressure, and the sensory motor system, which controls muscle movement. Where does brain store emotional memory which pairs the tone and shock. They began by making small lesions in different parts of the rats’ auditory systems to see if they could remove the conditioning response. When they lesioned auditory cortex rats still learned to fear the tone.
When they lesioned auditory thalamus, they eliminated the rats’ susceptibility to fear conditioning. They then found that, although most of the cells in the thalamus transmit to the cortex, some transmit to the amygdala, a region of the brain already implicated in various emotional behaviors. A lesion to the amygdala wiped out fear conditioning in the rats. In more specific studies, researchers found that they could eliminate various aspects of the fear response if they made lesions in specific areas downstream from the amygdala.
The amygdala receives auditory information from two different brain areas: the auditory thalamus and the auditory cortex. The amygdala then processes the signals and generates a fear response by stimulating other areas of the brain that control muscle function, heart rate and blood pressure. The signals coming from the thalamus reach the amygdala before signals from the cortex, but provide only general information about the incoming stimulus. In contrast, the signals from the cortex have longer latencies but provide detailed information about the stimulus. "The signals coming from the thalamus allow an animal to respond quickly without thinking too much first," said LeDoux. Then, as more information reaches the amygdala from the cortex, the animal can re-analyze the situation to determine if a threat really exists. This process is quite adaptive because it’s safer to respond quickly to a benign stimulus than to respond slowly to a true threat.
III Auditory cortex
Structure and function of auditory cortex
Cat is best known example, although bat studies have provided more ideas about function (but note that Pteronotus studies from Suga lab cannot at present be applied directly to cortical studies in other bats).
Basic organization and tonotopy
There are at least 7 complete tonotopic maps in cat including A1, AAF, A2, P, V and VP as well as Insular, Te and other anterior ectosylvian fields with uncertain tonotopy (Figure).
A1 and A2 share physiological features of alternating bands of EE and EI, run in A-P direction and orthogonal to tonotopic axis. Shamma here.
When compare with auditory nerve, cortical A1 responses more transient, show inhibition away from CF.
Physiology
Most responses binaural, preserving responses from brainstem.
Bat cortex organization (figures in handout). At least 7 areas.
Suga has described a parallel-hierarchical scheme for signal processing
Since the different CF and FM components differ in frequency, they are processed in parallel channels by virtue of their tonotopy
Can create combination sensitive neurons by comparing across frequency channels
Important principles for biologically important sounds (from Suga)
ADD SUGA SUMMARY HERE WHEN I GET TO WORK
Language and the Primate Brain (from Marty Sereno, abridged, most citations removed)
Add this to your reading; I probably won’t have time for it in class
http://crl.ucsd.edu/newsletter/4-4/Article1.html
Summary: Psychologists, neuropsychologists, and primate neurobiologists have studied human language comprehension and its relation to the primate brain in almost complete isolation from each other. Recent developments provide grounds for a new attempt at drawing some preliminary connections across the levels of organization spanned by these fields. New data on the large number of modality-specific areas in the post-central cortex of several non-human primates, and recent anatomical and functional studies of the human brain suggest that very little of the cortex consists of polymodal 'association' areas. These observations are used to reinterpret psychological and neuropsychological data on language comprehension in normal and brain-damaged humans. Sereno argues that language comprehension in sighted people might best be thought of as a kind of code-directed scene comprehension that draws heavily upon specifically visual, and probably largely prelinguistic processing constraints. The key processes of word-recognition and the assembly of visual word meaning patterns into interacting chains, however, may be mediated in part by species-specific activity patterns in secondary auditory cortex similar to those generated by uninterpreted speech-sound sequences.
One obvious reason to study non-human primate brains is that they resemble the human primate brain in many ways. Yet humans exhibit behaviors--especially the comprehension of linguistic discourse--that are qualitatively very different from behaviors of primates and other animals. Because of this, some have concluded that animal brains may be poor models for the human brain. There are presently quite substantial rifts between psychological, neuropsychological, and neurobiological approaches to language. Recent developments in studying human and animal brains, however, provide a strong impetus to re-open discourse among these disciplines.
The neocortex of all mammals is now known to consist primarily of a mosaic of visual, auditory, somatosensory, motor, and limbic areas. Primitive mammals have a small number of areas in each of these modalities, while carnivores and primates have many. In monkeys, for example, a mosaic of 25 visual areas occupies more than half of the entire neocortex. The traditional site for higher-level functions--"polymodal association cortex"--has been reduced to a few diminutive strips in between large expanses of unimodal visual, auditory, and somatosensory areas. The potential significance of this reparcellation of cortex for the study of language and the brain has hardly been explored. The aim of this paper is to re-introduce a comparative perspective into the evolutionary acquisition of the capacity for language, but one that does not back away from the obvious cognitive differences between humans and other animals. The anatomical and physiological organization of cortical areas in primates, including recent work on human cortex, is reviewed first. The implications of this work for theories of human language comprehension are then explored.
Cortical Sensory Areas in Primates - Definition of a Visual Area.
Cortical sensory areas are best defined by multiple converging criteria. I begin here with visual areas, since they constitute the largest of the primary sub- divisions of the cortex. Criteria for the definition of a visual area presently include architectonic features (e.g., degree of myelination, cell size, cell morphology, and cell packing density in cortical layers, histochemical features), connection patterns (e.g., input and output areas, laminar origins and targets of connections), visuotopic organization (e.g., mirror-image or non-mirror-image map of hemifield, bounding areas, pattern of map discontinuities, degree of retinotopy), and physiological properties (e.g., excitatory receptive field size, direction selectivity, attention- related modulation). Areas differ in the degree to which these criteria have been explored. V1 (primary visual cor- tex) and MT (middle temporal area) are distinct, well- studied areas in primates that are convergently identified by many of these criteria. Other areas--e.g., in inferotemporal cortex--are less well studied. There is no evidence to suggest that they are any less distinct. LOTS MORE LEFT OUT BY CEC
Auditory and Somatosensory Areas in Monkeys.
Auditory and somatosensory areas have been studied in parallel with visual areas. The main differences are the basis for topography (tonotopy and somatotopy vs. retinotopy), the one- dimensional nature of tonotopy (in contrast to two- dimensional retinotopy and somatotopy), the smaller overall size of auditory and somatosensory cortex, and the greater diversity of types of information collected by somatosensory receptor types (light touch, pain and temperature, muscle length changes, force on tendons, joint position). In both New and Old World monkeys, there are about 9 auditory cortical areas and about 9 somatosensory cortical areas. As in visual cortex, one can define a hierarchy of areas based on the laminar targets of between-area projections, and, as in vision, there is a successive loss of receptotopy as one progresses to higher levels in the two systems. Most of the somatosensory maps are based on responses to cutaneous stimulation (it is difficult to stimulate muscle and tendon receptors without also stimulating the skin).
These maps (and more fragmentary data from other species) suggest that the parcellation of most of the cortex has not changed radically during the evolution of the primate order. Notably, there does not seem to be any significant increase in the areas where several modalities overlap; rather, modality-specific areas have increased in size, and quite moderately in number; the number of cortical areas has probably not changed in New and Old World monkeys, which have evolved independently for over 30 million years.
Visual Areas in Apes and Humans.
The organization of the cortex in a variety of mammals including humans was studied extensively by Brodmann and others at the beginning of the century using stains for cell bodies and myelin (Brodmann, 1909). Since then, anatomical and physiological studies have revised many of Brodmann's conclusions with respect to non-human primate brains (e.g., Brodmann's area 18 in Old World monkeys is twice as wide as it should have been; Brodmann's area 19 actually contains many distinct cortical areas). But it is only very recently that human cortex has been approached from a modern perspective. Preliminary results suggest that human visual cortical areas are organized quite similarly to those of other primates.
MORE VISION TEXT OMITTED BY CARR
Language Processing in the Context of the Primate Brain. Modularity and Levels of Explanation.
The question of what language processing looks like in the brain is a contentious one, especially given the preliminary state of our current knowledge in this area. A certain tradition in cognitive science and neuropsychology seems to have taken as its goal, the isolation of higher levels of explanation from their lower level implementation. Such a so-called 'functional' approach is quite curious from a biological perspective. Surely, biologists are interested in function (e.g., the heart serves as a pump for blood). But the goal there is to try to explain how it is that the structure of the heart gives rise to its function--not to ignore that structure and build an independently motivated theory in a different language (a language of 'heart'?!). The fact that the same program can run on somewhat differently designed von Neumann machines (e.g., Fodor and Pylyshyn, 1988) seems an insufficient reason to abandon a biological and evolutionary approach to the functional organization of the human brain.
This tendency to ignore the structure of the brain is quite unfortunate in light of the recent progress made in primate neurobiology. Most current texts of physiological psychology, neuropsychology, and cognitive neuroscience still implicitly employ a model of the organization and evolution of the cortex that dates to the associationists of the late nineteenth century. In this way of thinking, 'primitive' mammals like rats start out with primary visual, auditory, and somatosensory areas almost touching. Next up the rung of an essentially pre-evolutionary scala natura come animals like cats, which have a small amount of 'uncommitted' space in between. Finally, at the top, are primates and especially humans, where we find a great deal of uncommitted 'association' cortex, properly situated to integrate and associate the modality-specific information presented to it by visual, auditory and somatosensory cortices (see e.g., Fodor, 1983; Ellis and Young, 1988, on the 'semantic system' postulated in most models of word processing; Damasio, 1989).
Fine-grained mapping experiments in hedgehogs, rodents, cats, and primates, during the past decade have shown this picture of the evolution of the cortex to be incorrect. Cats and primates do have more cortex in between the primary sensory areas; but that cortex consists not of polymodal association areas, but rather larger and more numerous modality-specific (i.e., visual, auditory, and somatosensory) areas. The studies discussed above provide no indication that humans are any different in this regard. The problem is, then, in the spirit of biological studies of functional organization, to try to describe how the basic anatomical modules of primate cortex--namely visual, auditory, somatosensory, motor, and limbic areas--support a new, peculiarly human function.
Language as Code-directed Scene Perception.
Vision is very important to primates; in fact, over 50% of the cortex in primates, probably including humans, consists of areas devoted to specifically visual processing. This is not to deny that information about an object perceived via another modality--say the somatosensory system--might be able to enter visual areas in the form of a visual copy of the somatosensory areas' activity pattern (see e.g., experiments by Haenny et al. (1988) in macaque visual area V4 using a somatosensory-visual matching task). But it does suggest that we carefully distinguish a visual copy of a somatosensory stimulus (in a visual area with a visual map) from a somatosensory copy of a visual stimulus (in a somatosensory area with a somatosensory map).
Some linguists have independently suggested that visual representations may be very important in the semantics of natural language. An idea common to several different approaches is that more concrete visual meanings may have been extended by analogical processes to deal with more abstract objects and relations. The present proposal goes further in suggesting a particularly direct relationship between the mechanisms of scene and discourse comprehension.
The integration of successive glances in the comprehension of a visual scene requires a kind of serial assembly operation similar in some respects to the integration of word meanings in discourse comprehension. Primates (but also many other animals) make long series of fixations at the rate of several new views per second during scene comprehension. Each fixation brings the retina to a new part of the visual scene and generates a burst of activity in V1, which largely replaces the burst caused by the previous fixation. Higher visual areas with less precise retinotopy somehow integrate information from these disconnected activity sequences to generate an internal representation of the location and identity of the relevant objects in the current scene (e.g., predators, food items, particular conspecifics, escape routes, suitable sleeping trees, etc.) that can serve as a basis for action. Many aspects of this process are redolent of linguistic integration--e.g., the underspecified, context-free information in an isolated glance is sharpened and focused by context (cf. polysemy); information from temporally distant glances must be tied together (cf. anaphora). None of this implies that scene representations (or their presumed linguistic fellows) need look anything like pictures; the patterns in question would be distributed across many areas, some of which show little retinotopy.
One main difference between scene and discourse comprehension is, of course, that scene comprehension is tied closely to the current scene. Discourse comprehension might best be thought of as a kind of fictive visual scene comprehension directed, in the case of spoken language comprehension, by sequences of phoneme representations in secondary auditory cortex. The advantage of linguistic discourse comprehension is that we are no longer tied to the current scene. However, once the appropriate visual word meaning patterns have been called up and bound together, the nature and interactions of the composite pattern may be conditioned mainly by the prelinguistic rules of interaction of scene representations in primate visual areas networks. In this sense, a large part of what has been called linguistic syntax and semantics might not be modular with respect to the neurobiology of vision.
There is in fact substantial evidence that visual areas in humans are involved in specifically linguistic functions. There is a kind of aphasia confusingly called 'transcortical sensory' aphasia (i.e., 'across-from-the-language-cortex' aphasia!) that is generated by a lesion in left human inferotemporal cortex (Rubens and Kertesz, 1983). Many of these lesions are so posterior and ventral that they are associated with overt visual field defects. Transcortical sensory aphasics have poor, "Wernicke's-like" comprehension, yet paradoxically (at least in the context of traditional models of language comprehension), can repeat words effortlessly. Far from being 'across from the language cortex', the visual areas in posterior inferotemporal cortex damaged in these patients may be the primary site of semantic processing in sighted humans. Transcortical sensory aphasics recover more quickly than patients with more dorsal lesions; this may only be an indication that the functions performed by visual cortex in language comprehension are less lateralized than those performed by auditory cortex. This is consistent with what we know about primate visual areas; permanent deficits in visual pattern recognition in monkeys require bilateral inferotemporal cortex lesions (Gross, 1973). There is no need to assume that all the cortical areas involved in language comprehension are equally lateralized; for example, the functions performed by the superior temporal gyrus (see below) may be more lateralized than the functions performed by the inferotemporal cortex.
Psycholinguistic experiments using pictures inserted into sentences and picture-word priming (Potter et al, 1986; Vanderwart, 1984) suggest that it is surprisingly easy for visually represented concepts to be integrated into ongoing linguistic discourse comprehension. This may be another indicator of the closeness of visual category representations to linguistic meanings.
Some PET Experiments.
Recently, it was suggested on the basis of PET experiments that semantic processing may be localized instead in the frontal lobe, just in front of "Broca's area" (Petersen et al., 1988; Posner et al., 1988). In the key experiment, subjects performed two tasks--1) repeating visually presented nouns, and 2) generating "uses" (related verbs) upon viewing an otherwise comparable series nouns. Upon subtracting these two conditions, an activated locus was uncovered in frontal cortex, just anterior to the representation of face, tongue, and throat muscles in primary motor cortex. Given the ease with which preparation for movement elicits strong activation in premotor areas (see e.g., Roland et al., 1980), however, it seems likely that the activity uncovered in this experiment actually represents the different motor programming demands of the two tasks. In the first case, a motor pattern is called up directly via over-learned connections between visual word shape and articulatory movements. In the second case, by contrast, the subject must make a new motor plan to say a word that is different from that which was viewed. In fact, the subject must also suppress an output that would normally be generated by looking at the first word (in the context of reading words aloud). Frontal cortex lesions in monkeys and man are known to especially impair the ability to make delayed responses. Given that posterior inferotemporal cortex has rarely if ever been selectively activated in a blood flow experiment, and that the PET technique has limited resolution, the activation underlying semantic processing may not yet have been seen. A posterior locus for semantics is more in line with the observation made long ago (and hardly overturned by more recent studies) that patients with large posterior lesions are generally much more impaired in extracting meaning from linguistic discourse--and surely seem to have a much more severe derangement of thought processes--than patients with large anterior lesions.
What's in Wernicke's Area?
Wernicke's area has occupied several different gyri over the years. Sometimes it is placed on the angular gyrus; sometimes it sits more anteriorly on the superior temporal gyrus; and often it sneaks across the superior temporal sulcus (the boundary between auditory cortical areas dorsally and visual cortical areas ventrally in primates) to sit partly in inferotemporal cortex. The left-right asymmetry originally demonstrated by Geschwind and Levitsky (1968) was in yet a different place-on the planum temporale (not even clearly visible in a lateral view). Several architectonic studies (Braak, 1978; Galaburda and Sanides, 1980) have identified a distinct area that shows a considerable left-right asymmetry (Braak's temporal magnopyramidal zone; Galaburda and Sanides' area Tpt) confined entirely to the posterior part of the lateral superior temporal gyrus. By comparison with other primates, this area is very likely to be a unimodal, secondary or tertiary auditory cortical area. Merzenich and Brugge (1973) recorded diffuse auditory responses from a geographically similar area in macaques.
If Wernicke's area proper (e.g., of Braak) is in fact a secondary or tertiary auditory area, we are left with something of a conundrum. Why should a lesion in an auditory area cause deficits in the assembly of the meaningful units of language? The deficits exhibited by many patients with a lesion in this area seem to extend beyond mere problems with auditory representations of words--their thoughts seem disarranged; often they are unable to manipulate even words with concrete visual meanings. The traditional conclusion has thus been that Wernicke's area must be an evolutionarily new 'language organ' not tied to one modality. A new interpretation more in line with the animal literature, is that the internal representations of speech sound sequences that a primate neurobiologist would expect to find in Wernicke's area proper must have some other function besides merely serving as internal copies of the speech stream; these uninterpreted speech sound representations must also be involved in word recognition and assembly of (primarily visual) meanings into coherent discourse structures. By this account, what distinguishes humans is the ability to use a sequence of symbol patterns from another modality to cause the assembly of meaning patterns in tertiary visual cortex. But the product of that assembly may be very similar to patterns assembled from direct visual inputs arriving via V1 during scene comprehension. The implication is that the trick of language was not to have invented the basic meaningful units but to have found a way of making standardized connections between them (see Sereno, 1986; 1990a; 1990b, for an extended discussion).
In monkeys, the superior temporal sulcus forms, as noted, the border between auditory and visual cortices. Since clinically defined Wernicke's-like aphasics often have lesions that extend into the inferotemporal region on the middle and inferior temporal gyri, a typical 'Wernicke's aphasia' may require damage to both the auditory cortex meaning assemblers and the visual cortex meanings they assemble.
New Routes Between Modalities.
In monkeys, one pathway responsible for cross-modal matching performance has been well-defined. Performance on somatosensory-visual matching tasks is catastrophically impaired by lesions to the basolateral amygdala (Murray and Mishkin, 1985). This part of the amygdala receives projections from secondary and tertiary visual, somatosensory, and auditory areas, and projects back to them. There is also a small polymodal strip on part of the upper bank of the superior temporal sulcus (e.g., Seltzer and Pandya, 1989). But this strip cannot by itself support cross-modal matching in monkeys.
The situation in humans must be somewhat different, at least with regard to the relative importance of the amygdala in one particular kind of cross-modal mapping that characterizes human language--the mapping between speech sounds and visual word meanings. The patient H.M. who had his amygdala removed bilaterally is quite unimpaired in recognizing visual objects named for him (or in naming visual objects himself). This suggests that humans must have a more robust connection between areas on either side of the superior temporal sulcus than monkeys do. Cross-modal matching experiments of the kind that amygdala-lesioned monkeys fail to perform have not yet been tried with H.M., and so the cross-modal pathway through the amygdala could very well still be important for some tasks in humans.
Conclusion
Language is recently derived; based on the evidence of stone tools and other more spectacular artifacts like cave paintings, it seems likely that peculiarly human cognition and presumably language use originated rather suddenly less than 50,000 to 100,000 years ago. In view of our knowledge of the strong similarities between the brains of various non-human primates, it seems unlikely that the cortex could have been completely reorganized in so short a time. Surely, there is no positive evidence for such a major reorganization. Recent evidence instead suggests that human and non-human primate brains are organized quite similarly. We need more attempts to explain the large qualitative differences between animal cognition and human language-based cognition as the result of relatively minor modifications and re-use of pre-existing primate neural circuitry (cf. Bates et al., 1989).
This paper suggests that it might be profitable to view language comprehension in sighted people as a kind of code directed scene comprehension taking place primarily in unimodal visual areas in posterior inferotemporal cortex. A second suggestion is that internal representation of speech sound chains in secondary auditory cortical areas (Wernicke's area proper) may have other functions besides merely serving as internal copies of the speech code chain; they may be intimately involved in word recognition and the binding together of visual cortex meaning patterns. Code directed pattern binding is clearly a specifically human faculty; but many of the constraints on the resulting bound-together patterns may reflect prelinguistic (nonmodular) constraints on interactions between activity patterns in tertiary visual areas. Studies of the connections of superior temporal sulcus region in humans--just now becoming possible--may throw more light on the presently obscure neural substrate of language and human thought.