Predictive Mouse Ultrasonic Vocalization Sequences: Uncovering Behavioral Significance, Auditory Cortex Neuronal Preferences, and Social-Experience-Driven Plasticity.

Mouse ultrasonic vocalizations (USVs) contain predictable sequential structures like bird songs and speech. Neural representation of USVs in the mouse primary auditory cortex (Au1) and its plasticity with experience has been largely studied with single-syllables or dyads, without using the predictability in USV sequences. Studies using playback of USV sequences have used randomly selected sequences from numerous possibilities. The current study uses mutual information to obtain context-specific natural sequences (NSeqs) of USV syllables capturing the observed predictability in male USVs in different contexts of social interaction with females. Behavioral and physiological significance of NSeqs over random sequences (RSeqs) lacking predictability were examined. Female mice, never having the social experience of being exposed to males, showed higher selectivity for NSeqs behaviorally and at cellular levels probed by expression of immediate early gene c-fos in Au1. The Au1 supragranular single units also showed higher selectivity to NSeqs over RSeqs. Social-experience-driven plasticity in encoding NSeqs and RSeqs in adult females was probed by examining neural selectivities to the same sequences before and after the above social experience. Single units showed enhanced selectivity for NSeqs over RSeqs after the social experience. Further, using two-photon Ca2+ imaging, we observed social experience-dependent changes in the selectivity of sequences of excitatory and somatostatin-positive inhibitory neurons but not parvalbumin-positive inhibitory neurons of Au1. Using optogenetics, somatostatin-positive neurons were identified as a possible mediator of the observed social-experience-driven plasticity. Our study uncovers the importance of predictive sequences and introduces mouse USVs as a promising model to study context-dependent speech like communications.SIGNIFICANCE STATEMENT Humans need to detect patterns in the sensory world. For instance, speech is meaningful sequences of acoustic tokens easily differentiated from random ordered tokens. The structure derives from the predictability of the tokens. Similarly, mouse vocalization sequences have predictability and undergo context-dependent modulation. Our work investigated whether mice differentiate such informative predictable sequences (NSeqs) of communicative significance from RSeqs at the behavioral, molecular, and neuronal levels. Following a social experience in which NSeqs occur as a crucial component, mouse auditory cortical neurons become more sensitive to differences between NSeqs and RSeqs, although preference for individual tokens is unchanged. Thus, speech-like communication and its dysfunction may be studied in circuit, cellular, and molecular levels in mice.

Separate Functional Subnetworks of Excitatory Neurons Show Preference to Periodic and Random Sound Structures.

Auditory cortex (ACX) neurons are sensitive to spectro-temporal sound patterns and violations in patterns induced by rare stimuli embedded within streams of sounds. We investigate the auditory cortical representation of repeated presentations of sequences of sounds with standard stimuli (common) with an embedded deviant (rare) stimulus in two conditions, Periodic (Fixed deviant position) or Random (Random deviant position). We used extracellular single-unit and two-photon Ca2+ imaging recordings in layer 2/3 neurons of the mouse (Mus musculus) ACX of either sex. Population single-unit average responses increased over repetitions in the Random condition and were suppressed or did not change in the Periodic condition, showing general irregularity preference. A subset of neurons showed the opposite behavior, indicating regularity preference. Furthermore, pairwise noise correlations were higher in the Random condition than in the Periodic condition, suggesting a role of recurrent connections in the observed differential adaptation. Functional two-photon Ca2+ imaging showed that excitatory (EX), and inhibitory (IN) neurons [parvalbumin-positive (PV) and somatostatin-positive (SOM)] also had different categories of long-term adaptation as observed with single-units. However, examination of functional connectivity between pairs of neurons of different categories showed that EX-PV connected pairs behaved opposite to the EX-EX and EX-SOM pairs, with more connections outside category in Random condition than Periodic condition. Finally, considering Regularity, Irregularity, and no preference of connected pairs of neurons showed that EX-EX and EX-SOM pairs were in largely separate functional subnetworks with different preferences, not EX-PV pairs. Thus, separate subnetworks underlie coding of periodic and random sound sequences.SIGNIFICANCE STATEMENT Studying how the auditory cortex (ACX) neurons respond to streams of sound sequences help us understand the importance of changes in dynamic acoustic noisy scenes around us. Humans and animals are sensitive to regularity and its violations in sound sequences. Psychophysical tasks in humans show that the auditory brain differentially responds to Periodic and Random structures, independent of the listener's attentional states. Here, we show that mouse ACX L2/3 neurons detect changes and respond differently to patterns over long-time scales. The differential functional connectivity profile obtained in response to two different sound contexts suggests the vital role of recurrent connections in the auditory cortical network. Furthermore, the excitatory-inhibitory neuronal interactions can contribute to detecting the changing sound patterns.

Earliest Experience of a Relatively Rare Sound But Not a Frequent Sound Causes Long-Term Changes in the Adult Auditory Cortex.

Sensory experience during a critical period alters sensory cortical responses and organization. We find that the earliest sound-driven activity in the mouse auditory cortex (ACX) starts before ear-canal opening (ECO). The effects of auditory experience before ECO on ACX development are unknown. We find that in mouse ACX subplate neurons (SPNs), crucial in thalamocortical maturation, respond to sounds before ECO showing oddball selectivity. Before ECO, SPNs are more selective to oddball sounds in auditory streams than thalamo-recipient layer 4 (L4) neurons and not after ECO. We hypothesize that SPN's oddball selectivity can direct the development of L4 responses before ECO. Exposing mice, of either sex, before ECO to a rarely occurring tone in a stream of another tone occurring frequently leads to strengthening the adult cortical representation of the rare tone, but not that of the frequent tone. Results of control exposure experiments at multiple developmental windows that also use only a single tone corroborate the observations. We further explain the strengthening of deviant inputs before ECO and not after ECO using a binary network model mimicking the hierarchical structure of subplate and L4 neurons and response properties derived from our data, with synapses following Hebbian spike time-dependent plasticity learning rule. Information-theoretic analysis with sparse coding assumptions also predicts the observations. Thus, relatively salient low probability sounds in the earliest auditory environment cause long-term changes in the ACX.SIGNIFICANCE STATEMENT Early auditory experience can change the organization and responses of the auditory cortex in adulthood. However, little is known about how auditory experience at prenatal ages changes neural circuits and response properties. In mice at equivalent early developmental stages, we find that auditory experience of a particular kind, with a less frequently occurring sound in a stream of another sound, alters adult cortical responsiveness, specifically of the less frequent sound. However, at the previously known critical period of development, the opposite is observed, where the more frequent sound's representation is strengthened in the adult compared with the less frequent sound. We thus show that a specific type of auditory environment can influence adult auditory processing at the earliest ages.

Frontal cortex activation causes rapid plasticity of auditory cortical processing.

Neurons in the primary auditory cortex (A1) can show rapid changes in receptive fields when animals are engaged in sound detection and discrimination tasks. The source of a signal to A1 that triggers these changes is suspected to be in frontal cortical areas. How or whether activity in frontal areas can influence activity and sensory processing in A1 and the detailed changes occurring in A1 on the level of single neurons and in neuronal populations remain uncertain. Using electrophysiological techniques in mice, we found that pairing orbitofrontal cortex (OFC) stimulation with sound stimuli caused rapid changes in the sound-driven activity within A1 that are largely mediated by noncholinergic mechanisms. By integrating in vivo two-photon Ca(2+) imaging of A1 with OFC stimulation, we found that pairing OFC activity with sounds caused dynamic and selective changes in sensory responses of neural populations in A1. Further, analysis of changes in signal and noise correlation after OFC pairing revealed improvement in neural population-based discrimination performance within A1. This improvement was frequency specific and dependent on correlation changes. These OFC-induced influences on auditory responses resemble behavior-induced influences on auditory responses and demonstrate that OFC activity could underlie the coordination of rapid, dynamic changes in A1 to dynamic sensory environments.

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

Objective. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effectively forming a network. The model demonstrates the occurrence of PIRE under strong inhibitory input. Emphasizing the significance of incorporating PIRE in neuromorphic circuits, the study showcases generation of persistent activity within cyclic and recurrent spiking neuronal networks.Approach. The neuronal and synaptic circuits are designed and simulated in Cadence Virtuoso using TSMC 180 nm technology. The operating mechanism of the PIRE phenomenon integrated into a hardware neuron is discussed. The proposed circuit encompasses several parameters for effectively controlling multiple electrophysiological features of a neuron.Main results. The neuronal circuit has been tuned to match the response of a biological neuron. The efficiency of this circuit is evaluated by computing the average power dissipation and energy consumption per spike through simulation. The sustained firing of neural spikes is observed till 1.7 s using the two neuronal networks.Significance. Persistent activity has significant implications for various cognitive functions such as working memory, decision-making, and attention. Therefore, hardware implementation of these functions will require our PIRE-integrated model. Energy-efficient neuromorphic systems are useful in many artificial intelligence applications, including human-machine interaction, IoT devices, autonomous systems, and brain-computer interfaces.

Changing microcircuits in the subplate of the developing cortex.

Subplate neurons (SPNs) are a population of neurons in the mammalian cerebral cortex that exist predominantly in the prenatal and early postnatal period. Loss of SPNs prevents the functional maturation of the cerebral cortex. SPNs receive subcortical input from the thalamus and relay this information to the developing cortical plate and thereby can influence cortical activity in a feedforward manner. Little is known about potential feedback projections from the cortical plate to SPNs. Thus, we investigated the spatial distribution of intracortical synaptic inputs to SPNs in vitro in mouse auditory cortex by photostimulation. We find that SPNs fell into two broad classes based on their distinct spatial patterns of synaptic inputs. The first class of SPNs receives inputs from only deep cortical layers, while the second class of SPNs receives inputs from deep as well as superficial layers including layer 4. We find that superficial cortical inputs to SPNs emerge in the second postnatal week and that SPNs that receive superficial cortical input are located more superficially than those that do not. Our data thus suggest that distinct circuits are present in the subplate and that, while SPNs participate in an early feedforward circuit, they are also involved in a feedback circuit at older ages. Together, our results show that SPNs are tightly integrated into the developing thalamocortical and intracortical circuit. The feedback projections from the cortical plate might enable SPNs to amplify thalamic inputs to SPNs.

Nonlinear temporal receptive fields of neurons in the dorsal cochlear nucleus.

Studies of the dorsal cochlear nucleus (DCN) have focused on spectral processing because of the complex spectral receptive fields of the DCN. However, temporal fluctuations in natural signals convey important information, including information about moving sound sources or movements of the external ear in animals like cats. Here, we investigate the temporal filtering properties of DCN principal neurons through the use of temporal weighting functions that allow flexible analysis of nonlinearities and time variation in temporal response properties. First-order temporal receptive fields derived from the neurons are sufficient to characterize their response properties to low-contrast (3-dB standard deviation) stimuli. Larger contrasts require the second-order terms. Allowing temporal variation of the parameters of the first-order model or adding a component representing refractoriness improves predictions by the model by relatively small amounts. The importance of second-order components of the model is shown through simulations of nonlinear envelope synchronization behavior across sound level. The temporal model can be combined with a spectral model to predict tuning to the speed and direction of moving sounds.

Contribution of the ventral pouch in the production of mouse ultrasonic vocalizations.

Mouse ultrasonic vocalizations (USVs) are of communicative significance and can serve as one of the major tools for behavioral phenotyping in mouse models of neurological disorders with social communication deficits. Understanding and identifying the mechanisms and role of laryngeal structures in generating USVs is crucial to understanding neural control of its production, which is likely dysfunctional in communication disorders. Although mouse USV production is accepted to be a whistle-based phenomenon, the class of whistle is debatable. Contradictory accounts exist on the role of a specific rodent intralaryngeal structure-the ventral pouch (VP), an air-sac-like cavity, and its cartilaginous edge. Also, inconsistencies in the spectral content of fictive USVs and real USVs in models without the VP points us to re-examine the role of the VP. We use an idealized structure, based on previous studies, to simulate a two-dimensional model of the mouse vocalization apparatus with the VP and without the VP. Our simulations were performed using comsol Multiphysics to examine characteristics of vocalizations beyond the peak frequency (f_{p}), like pitch jumps, harmonics, and frequency modulations, important in context-specific USVs. We successfully reproduced some of the crucial aspects of mouse USVs mentioned above, as observed through the spectrograms of simulated fictive USVs. Conclusions about the lack of a role of the mouse VP were previously made in studies primarily examining f_{p}. We investigated the impact of the intralaryngeal cavity and the alar edge on the simulated USV features beyond f_{p}. For the same combinations of parameters, removing the ventral pouch resulted in an alteration of the call characteristics, dramatically removing the variety of calls observed otherwise. Our results thus provide evidence supporting the hole-edge mechanism and the possible role of the VP in mouse USV production.

Sub-second temporal magnetic field microscopy using quantum defects in diamond.

Wide field-of-view magnetic field microscopy has been realised by probing shifts in optically detected magnetic resonance (ODMR) spectrum of Nitrogen Vacancy (NV) defect centers in diamond. However, these widefield diamond NV magnetometers require few to several minutes of acquisition to get a single magnetic field image, rendering the technique temporally static in it's current form. This limitation prevents application of diamond NV magnetometers to novel imaging of dynamically varying microscale magnetic field processes. Here, we show that the magnetic field imaging frame rate can be significantly enhanced by performing lock-in detection of NV photo-luminescence (PL), simultaneously over multiple pixels of a lock-in camera. A detailed protocol for synchronization of frequency modulated PL of NV centers with fast camera frame demodulation, at few kilohertz frequencies, has been experimentally demonstrated. This experimental technique allows magnetic field imaging of sub-second varying microscale currents in planar microcoils with imaging frame rates in the range of 50-200 frames per s (fps). Our work demonstrates that widefield per-pixel lock-in detection of frequency modulated NV ODMR enables dynamic magnetic field microscopy.

Parallel Lemniscal and Non-Lemniscal Sources Control Auditory Responses in the Orbitofrontal Cortex (OFC).

The orbitofrontal cortex (OFC) controls flexible behavior through stimulus value updating based on stimulus outcome associations, allowing seamless navigation in dynamic sensory environments with changing contingencies. Sensory cue driven responses, primarily studied through behavior, exist in the OFC. However, OFC neurons' sensory response properties, particularly auditory, are unknown in the mouse, a genetically tractable animal. We show that mouse OFC single neurons have unique auditory response properties showing pure oddball detection and long timescales of adaptation resulting in stimulus-history dependence. Further, we show that OFC auditory responses are shaped by two parallel sources in the auditory thalamus, lemniscal and non-lemniscal. The latter underlies a large component of the observed oddball detection and additionally controls persistent activity in the OFC through the amygdala. The deviant selectivity can serve as a signal for important changes in the auditory environment. Such signals, if coupled with persistent activity, obtained by disinhibitory control from the non-lemniscal auditory thalamus or amygdala, will allow for associations with a delayed outcome related signal, like reward prediction error, and potentially forms the basis of updating stimulus outcome associations in the OFC. Thus, the baseline sensory responses allow the behavioral requirement-based response modification through relevant inputs from other structures related to reward, punishment, or memory. Thus, alterations in these responses in neurologic disorders can lead to behavioral deficits.

Differential Rapid Plasticity in Auditory and Visual Responses in the Primarily Multisensory Orbitofrontal Cortex.

Given the connectivity of orbitofrontal cortex (OFC) with the sensory areas and areas involved in goal execution, it is likely that OFC, along with its function in reward processing, also has a role to play in perception-based multisensory decision-making. To understand mechanisms involved in multisensory decision-making, it is important to first know the encoding of different sensory stimuli in single neurons of the mouse OFC. Ruling out effects of behavioral state, memory, and others, we studied the anesthetized mouse OFC responses to auditory, visual, and audiovisual/multisensory stimuli, multisensory associations and sensory-driven input organization to the OFC. Almost all, OFC single neurons were found to be multisensory in nature, with sublinear to supralinear integration of the component unisensory stimuli. With a novel multisensory oddball stimulus set, we show that the OFC receives both unisensory as well as multisensory inputs, further corroborated by retrograde tracers showing labeling in secondary auditory and visual cortices, which we find to also have similar multisensory integration and responses. With long audiovisual pairing/association, we show rapid plasticity in OFC single neurons, with a strong visual bias, leading to a strong depression of auditory responses and effective enhancement of visual responses. Such rapid multisensory association driven plasticity is absent in the auditory and visual cortices, suggesting its emergence in the OFC. Based on the above results, we propose a hypothetical local circuit model in the OFC that integrates auditory and visual information which participates in computing stimulus value in dynamic multisensory environments.

Axon hillock currents enable single-neuron-resolved 3D reconstruction using diamond nitrogen-vacancy magnetometry.

Sensing neuronal action potential associated magnetic fields (APMFs) is an emerging viable alternative of functional brain mapping. Measurement of APMFs of large axons of worms have been possible due to their size. In the mammalian brain, axon sizes, their numbers and routes, restricts using such functional imaging methods. With a segmented model of mammalian pyramidal neurons, we show that the APMF of intra-axonal currents in the axon hillock are two orders of magnitude larger than other neuronal locations. Expected 2D magnetic field maps of naturalistic spiking activity of a volume of neurons via widefield diamond-nitrogen-vacancy-center-magnetometry were simulated. A dictionary-based matching pursuit type algorithm applied to the data using the axon-hillock's APMF signature allowed spatiotemporal reconstruction of action potentials in the volume of brain tissue at single cell resolution. Enhancement of APMF signals coupled with magnetometry advances thus can potentially replace current functional brain mapping techniques.

Male-specific alterations in structure of isolation call sequences of mouse pups with 16p11.2 deletion.

16p11.2 deletion is one of the most common gene copy variations that increases the susceptibility to autism and other neurodevelopmental disorders. This syndrome leads to developmental delays, including speech impairment and delays in expressive language and communication skills. To study developmental impairment of vocal communication associated with 16p11.2 deletion syndrome, we used the 16p11.2del mouse model and performed an analysis of pup isolation calls (PICs). The earliest PICs at postnatal day 5 from 16p11.2del pups were found altered in a male-specific fashion relative to wild-type (WT) pups. Analysis of sequences of ultrasonic vocalizations (USVs) emitted by pups using mutual information between syllables at different positions in the USV spectrograms showed that dependencies exist between syllables in WT mice of both sexes. The order of syllables was not random; syllables were emitted in an ordered fashion. The structure observed in the WT pups was identified and the pattern of syllable sequences was considered typical for the mouse line. However, typical patterns were totally absent in the 16p11.2del male pups, showing on average random syllable sequences, while the 16p11.2del female pups had dependencies similar to the WT pups. Thus, we found that PICs were reduced in number in male 16p11.2 pups and their vocalizations lack the syllable sequence order emitted by WT males and females and 16p11.2 females. Therefore, our study is the first to reveal sex-specific perinatal communication impairment in a mouse model of 16p11.2 deletion and applies a novel, more granular method of analysing the structure of USVs.

Converting waste Allium sativum peel to nitrogen and sulphur co-doped photoluminescence carbon dots for solar conversion, cell labeling, and photobleaching diligences: A path from discarded waste to value-added products.

Proper waste utilization in order to promote value added product is a promising scientific practice in recent era. Inspiring from the recurring trend, we propose a single step oxidative pyrolysis derived fluorescent carbon dots (C-dots) from Allium sativum peel, which is a natural, nontoxic, and waste raw material. Because of its excellent optical properties, and photostability this C-dots have been used in versatile area of applications. Due to its immediate water dispersing character, C-dots reinforced Poly(acrylic acid) (PAA) films revealed improvement in uniaxial stretching behavior and can be used as transparent sunlight conversion film. The nanocomposite film has been tested against rigorous simulated sunlight which proved almost identical sunlight conversion behavior with no photo-bleachable character which is definitely added an extra quality of transparent polymer films. Moreover, the C-dots dispersion has been used as in vitro biomarker for living cells owing to its ease in solubility, biocompatibility, non-cytotoxicity and bright fluorescence even in subcutaneous environment. For this case, adipose derived mesenchymal stem cells (ADMSCs) have been chosen and injected to rabbit ear skin to perform two-photon imaging experiment. The present work opens a new avenue towards the large-scale synthesis of bio-waste based fluorescent C-dots, paving the way for their versatile applications.

Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data.

Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall's tau , cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), k -nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the XY plane. However, outstanding gaps in the current literature have precluded the ability to effectively automate these methods, which, in turn, have caused limited adoptions by the application communities. This study attempts to address a key gap in the literature-specifically, the evaluation of the above methods to choose the best method, particularly in terms of their robustness for short and noisy data, based on comparisons with the theoretical MI estimates, which can be computed analytically, as well with linear correlation and Kendall's tau . Here we consider smaller data sizes, such as 50, 100, and 1000, and within this study we characterize 50 and 100 data points as very short and 1000 as short. We consider a broader class of functions, specifically linear, quadratic, periodic, and chaotic, contaminated with artificial noise with varying noise-to-signal ratios. Our results indicate KDEs as the best choice for very short data at relatively high noise-to-signal levels whereas the performance of KNNs is the best for very short data at relatively low noise levels as well as for short data consistently across noise levels. In addition, the optimal smoothing parameter of a Gaussian kernel appears to be the best choice for KDEs while three nearest neighbors appear optimal for KNNs. Thus, in situations where the approximate data sizes are known in advance and exploratory data analysis and/or domain knowledge can be used to provide a priori insights into the noise-to-signal ratios, the results in the paper point to a way forward for automating the process of MI estimation.

Ncm, a Photolabile Group for Preparation of Caged Molecules: Synthesis and Biological Application.

Ncm, 6-nitrocoumarin-7-ylmethyl, is a photolabile protective group useful for making "caged" molecules. Ncm marries the reliable photochemistry of 2-nitrobenzyl systems with the excellent stability and spectroscopic properties of the coumarin chromophore. From simple, commercially available starting materials, preparation of Ncm and its caged derivatives is both quick and easy. Photorelease of Ncm-caged molecules occurs on the microsecond time scale, with quantum efficiencies of 0.05-0.08. We report the synthesis and physical properties of Ncm and its caged derivatives. The utility of Ncm-caged glutamate for neuronal photostimulation is demonstrated in cultured hippocampal neurons and in brain slice preparations.

Discrimination of voiced stop consonants based on auditory nerve discharges.

Previous studies of the neural representation of speech assumed some form of neural code, usually discharge rate or phase locking, for the representation. In the present study, responses to five synthesized CVC_CV (e.g., /dad_da/) utterances have been examined using information-theoretic distance measures [or Kullback-Leibler (KL) distance] that are independent of a priori assumptions about the neural code. The consonants in the stimuli fall along a continuum from /b/ to /d/ and include both formant-frequency (F1, F2, and F3) transitions and onset (release) bursts. Differences in responses to pairs of stimuli, based on single-fiber auditory nerve responses at 70 and 50 dB sound pressure level, have been quantified, based on KL and KL-like distances, to show how each portion of the response contributes to information coding and the fidelity of the encoding. Distances were large at best frequencies, in which the formants differ but were largest for fibers encoding the high-frequency release bursts. Distances computed at differing time resolutions show significant information in the temporal pattern of spiking, beyond that encoded by rate, at time resolutions from 1-40 msec. Single-fiber just noticeable differences (JNDs) for F2 and F3 were computed from the data. These results show that F2 is coded with greater fidelity than F3, even among fibers tuned to F3, and that JNDs are larger in the syllable final consonant than in the releases.

Dichotomy of functional organization in the mouse auditory cortex.

The sensory areas of the cerebral cortex possess multiple topographic representations of sensory dimensions. The gradient of frequency selectivity (tonotopy) is the dominant organizational feature in the primary auditory cortex, whereas other feature-based organizations are less well established. We probed the topographic organization of the mouse auditory cortex at the single-cell level using in vivo two-photon Ca(2+) imaging. Tonotopy was present on a large scale but was fractured on a fine scale. Intensity tuning, which is important in level-invariant representation, was observed in individual cells, but was not topographically organized. The presence or near absence of putative subthreshold responses revealed a dichotomy in topographic organization. Inclusion of subthreshold responses revealed a topographic clustering of neurons with similar response properties, whereas such clustering was absent in supra-threshold responses. This dichotomy indicates that groups of nearby neurons with locally shared inputs can perform independent parallel computations in the auditory cortex.

Effects of stimulus spectral contrast on receptive fields of dorsal cochlear nucleus neurons.

Neurons in the dorsal cochlear nucleus (DCN) exhibit strong nonlinearities in spectral processing. Low-order models that transform the stimulus spectrum into discharge rate using a combination of first- and second-order weighting of the spectrum (quadratic models) usually fail to predict responses to novel stimuli for principal neurons in the DCN, even though they work well in ventral cochlear nucleus. Here we investigate the effects of spectral contrast on the performance of such models. Typically, the models fail for stimuli with natural-sound-like spectral contrasts (~12 dB), but have good prediction performance at small (3-dB) contrasts. The weights also typically increase substantially in amplitude at smaller spectral contrast. These changes in weight size with contrast are partly inherited from similar effects seen in auditory nerve fibers, but there must be additional effects from inhibitory circuits in the DCN. These results provide insight into the reasons for the poor performance of spectrotemporal receptive field (STRF) models in predicting responses of auditory neurons. Because the general shapes of the weights do not change between low and high contrast, they also suggest that STRFs may capture meaningful properties of neural receptive fields, even though they do not do well at predicting responses.

Receptive field for dorsal cochlear nucleus neurons at multiple sound levels.

Neurons in the dorsal cochlear nucleus (DCN) exhibit nonlinearities in spectral processing, which make it difficult to predict the neurons' responses to stimuli. Here, we consider two possible sources of nonlinearity: nonmonotonic responses as sound level increases due to inhibition and interactions between frequency components. A spectral weighting function model of rate responses is used; the model approximates the neuron's rate response as a weighted sum of the frequency components of the stimulus plus a second-order sum that captures interactions between frequencies. Such models approximate DCN neurons well at low spectral contrast, i.e., when the SD (contrast) of the stimulus spectrum is limited to 3 dB. This model is compared with a first-order sum with weights that are explicit functions of sound level, so that the low-contrast model is extended to spectral contrasts of 12 dB, the range of natural stimuli. The sound-level-dependent weights improve prediction performance at large spectral contrast. However, the interactions between frequencies, represented as second-order terms, are more important at low spectral contrast. The level-dependent model is shown to predict previously described patterns of responses to spectral edges, showing that small changes in the inhibitory components of the receptive field can produce large changes in the responses of the neuron to features of natural stimuli. These results provide an effective way of characterizing nonlinear auditory neurons incorporating stimulus-dependent sensitivity changes. Such models could be used for neurons in other sensory systems that show similar effects.