Model of discharge patterns of units in the cochlear nucleus in response to steady state and time-varying sounds

A model for the coding of sounds in the discharge pattern of single neurons in the auditory periphery is described. The model consists of a non-linear differential equation and a conventional diffusion neuron model. The same model describes 1) the unit interspike interval distribution in response to continuous stimulation, 2) the response to tone bursts, as well as 3) the responses to sinusoidally amplitude-modulated stimuli. The parameters of the model are determined quantitatively for each neuron. The responses of a certain unit can be described by 5 parameters.     

Mathematical models of cochlear nucleus onset neurons: I. Point neuron with many weak synaptic inputs

The cochlear nucleus (CN) presents a unique opportunity for quantitatively studying input-output transformations by neurons because it gives rise to a variety of different response types from a relatively homogeneous input source, the auditory nerve (AN). Particularly interesting among CN neurons are Onset (On) neurons, which have a prominent response to the onset of sustained sounds followed by little or no response in the steady-state. On neurons contrast sharply with their AN inputs, which respond vigorously throughout stimuli. On neurons can entrain to stimuli (firing once per cycle of a periodic stimulus) at up to 1000 Hz, unlike their AN inputs. To understand the mechanisms underlying these response patterns, we tested whether an integrate-to-threshold point-neuron model with a fixed refractory period can account for On discharge patterns for tones, systematically examining the effect of membrane time constant and the number and strength of the exclusively excitatory AN synaptic inputs. To produce both onset responses to high-frequency tone bursts and entrainment to a broad range of low-frequency tones, the model must have a short time constant (0.125 ms) and a large number (>100) of weak synaptic inputs, properties that are consistent with the electrical properties and anatomy of On-responding cells. With these parameters, the model acts like a coincidence detector with a threshold-like relationship between the instantaneous discharge rates of the output and the inputs. Onset responses to high-frequency tone bursts result because the threshold effect enhances the initial response of the AN inputs and suppresses their relatively lower sustained response. However, when the model entrains across a broad range of frequencies, it also produces short interspike intervals at the onset of high-frequency tone bursts, a response pattern not found in all types of On neurons. These results show a tradeoff, that may be a general property of many neurons, between following rapid stimulus fluctuations and responding without short interspike intervals at the onset of sustained stimuli.     

Encoding properties of auditory neurons in the brain of a soniferous damselfish: response to simple tones and complex conspecific signals

The fish auditory system encodes important acoustic stimuli used in social communication, but few studies have examined response properties of central auditory neurons to natural signals. We determined the features and responses of single hindbrain and midbrain auditory neurons to tone bursts and playbacks of conspecific sounds in the soniferous damselfish, Abudefduf abdominalis. Most auditory neurons were either silent or had slow irregular resting discharge rates <20 spikes s⁻¹. Average best frequency for neurons to tone stimuli was ~130 Hz but ranged from 80 to 400 Hz with strong phase-locking. This low-frequency sensitivity matches the frequency band of natural sounds. Auditory neurons were also modulated by playbacks of conspecific sounds with thresholds similar to 100 Hz tones, but these thresholds were lower than that of tones at other test frequencies. Thresholds of neurons to natural sounds were lower in the midbrain than the hindbrain. This is the first study to compare response properties of auditory neurons to both simple tones and complex stimuli in the brain of a recently derived soniferous perciform that lacks accessory auditory structures. These data demonstrate that the auditory fish brain is most sensitive to the frequency and temporal components of natural pulsed sounds that provide important signals for conspecific communication.     

Peripheral specialization for fine analysis of doppler-shifted echoes in the auditory system of the "CF-FM" bat Pteronotus parnellii.

Pteronotus parnellii uses the second harmonic (61-62 kHz) of the CF component in its orientation sounds for Doppler-shift compensation. The bat's inner ear is mechanically specialized for fine analysis of sounds at about 61-62 kHz. Because of this specialization, cochlear microphonics (CM) evoked by 61-62 kHz tone bursts exhibit prominent transients, slow increase and decrease in amplitude at the onset and cessation of these stimuli. CM-responses to 60-61 kHz tone bursts show a prominent input-output non-linearity and transients. Accordingly, a summated response of primary auditory neurones (N1) appears not only at the onset of the stimuli, but also at the cessation. N1-off is sharply tuned at 60-61 kHz, while N1-on is tuned at 63-64 kHz, which is 2 kHz higher than the best frequency of the auditory system because of the envelope-distortion originating from sharp mechanical tuning. Single peripheral neurones sensitive to 61-62 kHz sounds have an unusually sharp tuning curve and show phase-locked responses to beats of up to 3 kHz. Information about the frequencies of Doppler-shifted echoes is thus coded by a set of sharply tuned neurones and also discharges phase-locked to beats. Neurones with a best frequency between 55 and 64 kHz show not only tonic on-responses but also off-responses which are apparently related to the mechanical off-transient occuring in the inner ear and not to a rebound from neural inhibition.     

Feature-detecting auditory neurons in the brain of a sound-producing fish

The mormyrid fish Pollimyrus adspersus has auditory specializations for sound pressure detection and uses acoustic displays in its natural social behavior. In this paper it is shown that auditory neurons in the mesencephalon (torus semicircularis) are activated selectively by temporal features of complex sounds. Single neurons were recorded while presenting sounds to fish underwater. The stimuli were acoustic click trains, 400 ms in duration, and were synthesized with differing inter-click-intervals (ICIs). The natural sounds of this species are composed similarly and the range of ICIs synthesized overlapped with the natural range (5–40 ms). One-third of the neurons studied were strongly selective for a narrow range of ICIs, increasing spike rate by ten fold or more at the best ICI compared to the minimum response observed. The best ICI for interval selective neurons remained stable when the sound pressure of the stimulus was changed. Neurons that were selective gave phasic responses to tone bursts, and most had non-monotonic rate level functions. The origin of interval selectivity is discussed and a time-based computational mechanism is proposed. Accepted: 20 December 1996     

Differences between Spectro-Temporal Receptive Fields Derived from Artificial and Natural Stimuli in the Auditory Cortex

Spectro-temporal properties of auditory cortex neurons have been extensively studied with artificial sounds but it is still unclear whether they help in understanding neuronal responses to communication sounds. Here, we directly compared spectro-temporal receptive fields (STRFs) obtained from the same neurons using both artificial stimuli (dynamic moving ripples, DMRs) and natural stimuli (conspecific vocalizations) that were matched in terms of spectral content, average power and modulation spectrum. On a population of auditory cortex neurons exhibiting reliable tuning curves when tested with pure tones, significant STRFs were obtained for 62% of the cells with vocalizations and 68% with DMR. However, for many cells with significant vocalization-derived STRFs (STRF_voc) and DMR-derived STRFs (STRF_dmr), the BF, latency, bandwidth and global STRFs shape differed more than what would be predicted by spiking responses simulated by a linear model based on a non-homogenous Poisson process. Moreover STRF_voc predicted neural responses to vocalizations more accurately than STRF_dmr predicted neural response to DMRs, despite similar spike-timing reliability for both sets of stimuli. Cortical bursts, which potentially introduce nonlinearities in evoked responses, did not explain the differences between STRF_voc and STRF_dmr. Altogether, these results suggest that the nonlinearity of auditory cortical responses makes it difficult to predict responses to communication sounds from STRFs computed from artificial stimuli.     

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons'' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.     

刺激大鼠杏仁外侧核对皮层AⅠ区ON-OFF神经元反应及调谐曲线的影响

在30只氨基甲酸乙酯麻醉的SD大鼠上记录神经元单位放电,观察短纯音诱发的皮层AI区神经元ON－OFF反应的特性及电刺激杏仁外侧核（lateral amygdaloid nucleus,LA)对ON－OFF反应以及调谐曲线的影响。实验证实,AI区神经元ON－OFF反应的模式与纯音刺激的强度、频率及作用时程有关;刺激LA可以抑制ON－OFF反应的放电频数,使反应的阈值升高,或使反应放电构型发生变化;此外,刺激LA能使ON－OFF神经元的调谐曲线变窄,Q10数值增大。研究结果不仅表明ON－OFF神经元能对纯音刺激的时程、强度和频率等多种信息进行编码,而且还证明杏仁外侧核可以在皮层水平参与听觉信息的调制,削弱或衰减某些听觉信息,导致整个调谐曲线上移变窄,从而提高AI区ON－OFF神经元的频率选择性能,有利于检测外界嘈杂环境中特定的听觉信息。     

Response variability in the mammalian auditory cortex: an objection to feature detection?

Research strategy in the auditory system has tended to parallel that in the visual system, where neurons have been shown to respond selectively to specific stimulus parameters. Auditory neurons have been shown to be sensitive to changes in acoustic parameters, but only rarely have neurons been reported that respond exclusively to only one biologically significant sound. Even at higher levels of the auditory system very few cells have been found that could be described as "vocalization detectors." In addition, variability in responses to artificial sounds have been reported for auditory cortical neurons similar to the response variability that has been reported in the visual system. Recent evidence indicates that the responses of auditory cortical neurons to species-specific vocalizations can also be labile, varying in both strength and selectivity. This is especially true of the secondary auditory cortex. This variability, coupled with the lack of extreme specificity in the secondary auditory cortex, suggests that secondary cortical neurons are not well suited for the role of "vocalization detectors."     

Serotonin modulates responses to species-specific vocalizations in the inferior colliculus

Neuromodulators such as serotonin are capable of altering the neural processing of stimuli across many sensory modalities. In the inferior colliculus, a major midbrain auditory gateway, serotonin alters the way that individual neurons respond to simple tone bursts and linear frequency modulated sweeps. The effects of serotonin are complex, and vary among neurons. How serotonin transforms the responses to spectrotemporally complex sounds of the type normally heard in natural settings has been poorly examined. To explore this issue further, the effects of iontophoretically applied serotonin on the responses of individual inferior colliculus neurons to a variety of recorded species-specific vocalizations were examined. These experiments were performed in the Mexican free-tailed bat, a species that uses a rich repertoire of vocalizations for the purposes of communication as well as echolocation. Serotonin frequently changed the number of recorded calls that were capable of evoking a response from individual neurons, sometimes increasing (15% of serotonin-responsive neurons), but usually decreasing (62% of serotonin-responsive neurons), this number. A functional consequence of these serotonin-evoked changes would be to change the population response to species-specific vocalizations.     

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Sensory neurons encode natural stimuli by changes in firing rate or by generating specific firing patterns, such as bursts. Many neural computations rely on the fact that neurons can be tuned to specific stimulus frequencies. It is thus important to understand the mechanisms underlying frequency tuning. In the electrosensory system of the weakly electric fish, Apteronotus leptorhynchus, the primary processing of behaviourally relevant sensory signals occurs in pyramidal neurons of the electrosensory lateral line lobe (ELL). These cells encode low frequency prey stimuli with bursts of spikes and high frequency communication signals with single spikes. We describe here how bursting in pyramidal neurons can be regulated by intrinsic conductances in a cell subtype specific fashion across the sensory maps found within the ELL, thereby regulating their frequency tuning. Further, the neuromodulatory regulation of such conductances within individual cells and the consequences to frequency tuning are highlighted. Such alterations in the tuning of the pyramidal neurons may allow weakly electric fish to preferentially select for certain stimuli under various behaviourally relevant circumstances.     

Multiple specializations in the peripheral auditory system of the CF-FM bat,Pteronotus parnellii

Summary Cochlear microphonic (CM) and evoked neural potentials (N₁) were recorded from the cochlear aqueduct of awakePteronotus parnellii. The CM audiograms obtained with continuous sounds had more or less uniform thresholds except for a sharp threshold notch at about 60 kHz (Fig. 1). When brief tone bursts were presented, the envelopes of the CM responses were always similar to the envelopes of the applied signals except when tone bursts having frequencies at or close to the frequency of the tuned sensitivity notch were presented (i.e., 59–63 kHz). The CM rise-decay times for frequencies around 60kHz were much longer than those of the presented signals (Fig. 2). The prolonged decay times are thought to be due to the ringing of the basilar membrane resulting from a mechanical resonance in the cochlea.The evoked neural potential audiograms (N₁-on and N₁-off responses) differed considerably from the CM audiogram. Of particular importance is the N₁-off audiogram which exhibited very sharp tuning in four frequency regions: 31–33 kHz, 60–63 kHz, 71–73 kHz, and 91–92 kHz (Fig. 5). The frequencies evoking the lowest thresholds of the CM and N₁-off (in the 60 kHz region) were either identical or differed by only 100–400 Hz.The sharp tuning in the 60 kHz region of both the CM and N₁ audiograms could be eliminated by presenting 90–100 dB continuous sounds for one min but only if the signal frequency was equal to the tuned frequency of the CM audiogram (Figs. 8–13). Presenting intense sounds having frequencies above or below the tuned 60kHz region had no effect on the audiogram. The overstimulation procedure had remarkably specific effects on the CM and N₁-off audiograms causing the greatest threshold increases at the 60 kHz tuned frequency and progressively smaller threshold changes on the slopes of the tuned notch.Assuming that the sharp changes of the N₁-off thresholds reflect some important underlying mechanism, the N₁-off audiograms demonstrate multiple specializations in the peripheral auditory system ofPteronotus with the bat possessing at least three and possibly four sharply tuned regions. With regard to mechanism, the tuned notch in the CM audiogram, the curious CM rise-decay times evoked by tone bursts, and the ease with which the 60 kHz sensitivity notch can be eliminated all argue strongly in favor of a mechanical resonance in the cochlea which is responsible for the sharp tuning around 60 kHz. On the other hand, the absence of tuned notches in the 30 kHz and 90 kHz regions of the CM audiogram together with the absence of any discernable ringing of the CM potentials evoked by 30 kHz and 90 kHz tone bursts both argue against a resonance mechanism for the tuning at these harmonically related frequency regions. Finally, the fact that overstimulating the 60 kHz region had no discernable effect on the N₁-off tuning at 30 kHz and 90 kHz demonstrates that the mechanism responsible for the tuned regions at 30 kHz and 90 kHz are independent of the resonance feature of the cochlea at 60 kHz.Abbreviations BF best frequency - CF constant frequency - CM cochlear microphonics - CM-aft after-response of the CM - FM frequency modulated - N ₁ evoked neural potentials We thank Professor Alvin Novick for the generous support provided during the conduct of these experiments. We also thank Professor Gerhard Neuweiler and Dr. Gerd Schuller for their helpful comments and suggestions. Supported by PHS Grant NB7616 11.     

Modeling complex tone perception: grouping harmonics with combination-sensitive neurons

 Perception of complex communication sounds is a major function of the auditory system. To create a coherent percept of these sounds the auditory system may instantaneously group or bind multiple harmonics within complex sounds. This perception strategy simplifies further processing of complex sounds and facilitates their meaningful integration with other sensory inputs. Based on experimental data and a realistic model, we propose that associative learning of combinations of harmonic frequencies and nonlinear facilitation of responses to those combinations, also referred to as “combination-sensitivity,” are important for spectral grouping. For our model, we simulated combination sensitivity using Hebbian and associative types of synaptic plasticity in auditory neurons. We also provided a parallel tonotopic input that converges and diverges within the network. Neurons in higher-order layers of the network exhibited an emergent property of multifrequency tuning that is consistent with experimental findings. Furthermore, this network had the capacity to “recognize” the pitch or fundamental frequency of a harmonic tone complex even when the fundamental frequency itself was missing. Received: 6 October 2001 / Accepted in revised form: 21 January 2002     

Eye position influences auditory responses in primate inferior colliculus

We examined the frame of reference of auditory responses in the inferior colliculus in monkeys fixating visual stimuli at different locations. Eye position modulated the level of auditory responses in 33% of the neurons we encountered, but it did not appear to shift their spatial tuning. The effect of eye position on auditory responses was substantial-comparable in magnitude to that of sound location. The eye position signal appeared to interact with the auditory responses in at least a partly multiplicative fashion. We conclude that the representation of sound location in primate IC is distributed and that the frame of reference is intermediate between head- and eye-centered coordinates. The information contained in these neurons appears to be sufficient for later neural stages to calculate the positions of sounds with respect to the eyes.     

Neurons with different temporal firing patterns in the inferior colliculus of the little brown bat differentially process sinusoidal amplitude-modulated signals

We examined how well single neurons in the inferior colliculus (IC) of an FM bat (Myotis lucifugus) processed simple tone bursts of different duration and sinusoidal amplitude-modulated (SAM) signals that approximated passively heard natural sounds. Units' responses to SAM tones, measured in terms of average spike count and firing synchrony to the modulation envelope, were plotted as a function of the modulation frequency to construct their modulation transfer functions. These functions were classified according to their shape (e.g., band-, low-, high-, and all-pass). IC neurons having different temporal firing patterns to simple tone bursts (tonic, chopper, onset-late, and onset-immediate) exhibited different selectivities for SAM signals. All tonic and 83% of chopper neurons responded robustly to SAM signals and displayed a variety of spike count-based response functions. These neurons showed a decreased level of time-locking as the modulation frequency was increased, and thereby gave low-pass synchronization-based response functions. In contrast, 64% of onset-immediate, 37% of onset-late and 17% of chopper units failed to respond to SAM signals at any modulation frequency tested (5–800 Hz). Those onset neurons that did respond to SAM showed poor time-locking (i.e., non-significant levels of synchronization). We obtained evidence that the poor SAM response of some onset and chopper neurons was due to a preference for short-duration signals. These data suggest that tonic and most chopper neurons are better-suited for the processing of long-duration SAM signals related to passive hearing, whereas onset neurons are better-suited for the processing of short, pulsatile signals such as those used in echolocation.Abbreviations C chopper - FM frequency-modulated - IC inferior colliculus - MTF modulation transfer function - O₁ onset-immediate - O_L onset-late - PAM pulsatile amplitude-modulation - PSTH peri-stimulus time histogram - SAM sinusoidal amplitude-modulation - SC synchronization coefficient - T tonic     

The effect of pulse repetition rate on the delay sensitivity of neurons in the auditory cortex of the FM bat,Myotis lucifugus

1. Echo delay is the primary cue used by echolocating bats to determine target range. During target-directed flight, the repetition rate of pulse emission increases systematically as range decreases. Thus, we examined the delay tuning of 120 neurons in the auditory cortex of the bat, Myotis lucifugus, as repetition rate was varied. 2. Delay sensitivity was exhibited in 77% of the neurons over different ranges of pulse repetition rates (PRRs). Delay tuning typically narrowed and eventually disappeared at higher PRRs. 3. Two major types of delay-sensitive neurons were found: i) delay-tuned neurons (59%) had a single fixed best delay, while ii) tracking neurons (22%) changed their best delay with PRR. 4. PRRs from 1-100/s were represented by the population of delay-sensitive neurons, with the majority of neurons delay-sensitive at PRRs of at least 10-20/s. Thus, delay-dependent neurons in Myotis are most active during the search phase of echolocation. 5. Delay-sensitive neurons that also responded to single sounds were common. At PRRs where delay sensitivity was found, the responses to single sounds were reduced and the responses to pulse-echo pairs at particular delays were greater than the single-sound responses. In facilitated neurons (53%), the maximal delay-dependent response was always larger than the best single-sound responses, whereas in enhanced neurons (47%), these responses were comparable. The presence of neurons that respond maximally to single sounds at one PRR and to pulse-echo pairs with particular echo delays at other PRRs suggests that these neurons perform echo-ranging in conjunction with other biosonar functions during target pursuit.     

Auditory processing of complex sounds: an overview.

The past 30 years has seen a remarkable development in our understanding of how the auditory system--particularly the peripheral system--processes complex sounds. Perhaps the most significant has been our understanding of the mechanisms underlying auditory frequency selectivity and their importance for normal and impaired auditory processing. Physiologically vulnerable cochlear filtering can account for many aspects of our normal and impaired psychophysical frequency selectivity with important consequences for the perception of complex sounds. For normal hearing, remarkable mechanisms in the organ of Corti, involving enhancement of mechanical tuning (in mammals probably by feedback of electro-mechanically generated energy from the hair cells), produce exquisite tuning, reflected in the tuning properties of cochlear nerve fibres. Recent comparisons of physiological (cochlear nerve) and psychophysical frequency selectivity in the same species indicate that the ear's overall frequency selectivity can be accounted for by this cochlear filtering, at least in bandwidth terms. Because this cochlear filtering is physiologically vulnerable, it deteriorates in deleterious conditions of the cochlea--hypoxia, disease, drugs, noise overexposure, mechanical disturbance--and is reflected in impaired psychophysical frequency selectivity. This is a fundamental feature of sensorineural hearing loss of cochlear origin, and is of diagnostic value. This cochlear filtering, particularly as reflected in the temporal patterns of cochlear fibres to complex sounds, is remarkably robust over a wide range of stimulus levels. Furthermore, cochlear filtering properties are a prime determinant of the 'place' and 'time' coding of frequency at the cochlear nerve level, both of which appear to be involved in pitch perception. The problem of how the place and time coding of complex sounds is effected over the ear's remarkably wide dynamic range is briefly addressed. In the auditory brainstem, particularly the dorsal cochlear nucleus, are inhibitory mechanisms responsible for enhancing the spectral and temporal contrasts in complex sounds. These mechanisms are now being dissected neuropharmacologically. At the cortical level, mechanisms are evident that are capable of abstracting biologically relevant features of complex sounds. Fundamental studies of how the auditory system encodes and processes complex sounds are vital to promising recent applications in the diagnosis and rehabilitation of the hearing impaired.     

Frequency resolution and spectral integration (critical band analysis) in single units of the cat primary auditory cortex

Frequency resolution and spectral filtering in the cat primary auditory cortex (AI) were mapped by extracellular recordings of tone responses in white noise of various bandwidths. Single-tone excitatory tuning curves, critical bandwidths, and critical ratios were determined as a function of neuronal characteristic frequency and tone level. Single-tone excitatory tuning curves are inadequate measures of frequency resolution and spectral filtering in the AI, because their shapes (in most neurons) deviated substantially from the shapes of “tuning curves for complex sound analysis”, the curves determined by the band limits of the critical bandwidths. Perceptual characteristics of spectral filtering (intensity independence and frequency dependence) were found in average critical bandwidths of neurons from the central and ventral AI. The highest frequency resolution (smallest critical bandwidths) reached by neurons in the central and ventral AI equaled the psychophysical frequency resolution. The dorsal AI is special, since most neurons there had response properties incompatible with psychophysical features of frequency resolution. Perceptual characteristics of critical ratios were not found in the average neuronal responses in any area of the AI. It seems that spectral integration in the way proposed to be the basis for the perception of tones in noise is not present at the level of the AI. Accepted: 21 July 1997     

Responses of midbrain auditory neurons in rats to FM and AM tones presented simultaneously

Speech and other communication signals contain components of frequency and amplitude modulations (FM, AM) that often occur together. Auditory midbrain (or inferior colliculus, IC) is an important center for coding time-varying features of sounds. It remains unclear how IC neurons respond when FM and AM stimuli are both presented. Here we studied IC neurons in the urethane-anesthetized rats when animals were simultaneously stimulated with FM and AM tones. Of 122 units that were sensitive to the dual stimuli, the responses could be grossly divided into two types: one that resembled the respective responses to FM or AM stimuli presented separately ("simple" sensitivity, 45% of units), and another that appeared markedly different from their respective responses to FM or AM tones ("complex" sensitivity, 55%). These types of combinational sensitivities were further correlated with individual cell's frequency tuning pattern (response area) and with their common response pattern to FM and AM sounds. Results suggested that such combinational sensitivity could reflect local synaptic interactions on IC neurons and that the neural mechanisms could underlie more developed sensitivities to acoustic combinations found at the auditory cortex.     

A computational model of rapid task-related plasticity of auditory cortical receptive fields

Receptive field properties of neurons in A1 can rapidly adapt their shapes during task performance in accord with specific task demands and salient sensory cues (Fritz et al., Hearing Research, 206:159–176, 2005a, Nature Neuroscience, 6: 1216–1223, 2003). Such modulatory changes selectively enhance overall cortical responsiveness to target (foreground) sounds and thus increase the likelihood of detection against the background of reference sounds. In this study, we develop a mathematical model to describe how enhancing discrimination between two arbitrary classes of sounds can lead to the observed receptive field changes in a variety of spectral and temporal discrimination tasks. Cortical receptive fields are modeled as filters that change their spectro-temporal tuning properties so as to respond best to the discriminatory acoustic features between foreground and background stimuli. We also illustrate how biologically plausible constraints on the spectro-temporal tuning of the receptive fields can be used to optimize the plasticity. Results of the model simulations are compared to published data from a variety of experimental paradigms.