Single Unit publications

Intracortical microelectrode arrays record multi-unit extracellular activity for neurophysiology studies and for brain-machine interface applications. The common first step is neural spike-detection; a process complicated by common-noise signals from motion artifacts, electromyographic activity, and electric field pickup, especially in awake/behaving subjects. Often common-noise spikes are very similar to neural spikes in their magnitude, spectral, and temporal features. Provided sufficient spacing exists between electrodes of the array, a local neural spike is rarely recorded on multiple electrodes simultaneously. This is not true for distant common-noise sources. Two new techniques compatible with standard spike-detection schemes are introduced and evaluated. The first method, virtual referencing (VR), takes the average recording from all functional electrodes in the array (represents the signal from a virtual-electrode at the array's center) and subtracts it from the test electrode signal. The second method, inter-electrode correlation (IEC), computes a correlation coefficient between threshold exceeding candidate spike segments on the test electrode and concurrent segments from remaining electrodes. When sufficient correlation is detected, the candidate spike is rejected as originating from a distant common-noise source. The performance of these algorithms was compared with standard thresholding and differential referencing approaches using neural recordings from un-anaesthetized rats. By evaluating characteristics of mean-spike waveforms generated by each method under different levels of common-noise, it was found that IEC consistently offered the most robust means of neural spike-detection. Furthermore, IEC's rejection of supra-threshold events not likely originating from local neurons significantly reduces data handling for downstream spike sorting and processing operations.

Any sound can be separated mathematically into a slowly varying envelope and rapidly varying fine-structure component. This property has motivated numerous perceptual studies to understand the relative importance of each component for speech and music perception. Specialized acoustic stimuli, such as auditory chimaeras with the envelope of one sound and fine structure of another have been used to separate the perceptual roles for envelope and fine structure. Cochlear narrowband filtering limits the ability to isolate fine structure from envelope; however, envelope recovery from fine structure has been difficult to evaluate physiologically. To evaluate envelope recovery at the output of the cochlea, neural cross-correlation coefficients were developed that quantify the similarity between two sets of spike-train responses. Shuffled auto- and cross-correlogram analyses were used to compute separate correlations for responses to envelope and fine structure based on both model and recorded spike trains from auditory nerve fibers. Previous correlogram analyses were extended to isolate envelope coding more effectively in auditory nerve fibers with low center frequencies, which are particularly important for speech coding. Recovered speech envelopes were present in both model and recorded responses to one- and 16-band speech fine-structure chimaeras and were significantly greater for the one-band case, consistent with perceptual studies. Model predictions suggest that cochlear recovered envelopes are reduced following sensorineural hearing loss due to broadened tuning associated with outer-hair cell dysfunction. In addition to the within-fiber cross-stimulus cases considered here, these neural cross-correlation coefficients can also be used to evaluate spatiotemporal coding by applying them to cross-fiber within-stimulus conditions. Thus, these neural metrics can be used to quantitatively evaluate a wide range of perceptually significant temporal coding issues relevant to normal and impaired hearing.

Competing theories seek to account for the therapeutic effects of high-frequency deep brain stimulation (DBS) of the internal globus pallidus (GPi) for medically intractable Parkinson's disease. To investigate this question, we studied the spontaneous activity of 102 pallidal neurons during GPiDBS in two macaques rendered parkinsonian by administration of MPTP. Stimulation through macroelectrodes in the GPi (≥200 μA at 150 Hz for 30 s) reduced rigidity in one animal and increased spontaneous movement in both. Novel artifact subtraction methods allowed uninterrupted single-unit recording during stimulation. GPiDBS induced phasic (78% of cells) or sustained (22%) peristimulus changes in firing in both pallidal segments. A subset of cells responded at short latency (<2 ms) in a manner consistent with antidromic driving. Later phasic increases clustered at 3- to 5-ms latency. Stimulation-induced decreases were either phasic, clustered at 1–3 ms, or sustained, showing no peristimulus modulation. Response latency and magnitude often evolved over 30 s of stimulation, but responses were relatively stable by the end of that time. GPiDBS reduced mean firing rates modestly and only in GPi (−6.9 spikes/s). Surprisingly, GPiDBS had no net effect on the prevalence or structure of burst firing. GPiDBS did reduce the prevalence of synchronized low-frequency oscillations. Some cell pairs became synchronized instead at the frequency of stimulation. Suppression of low-frequency oscillations did not require high-frequency synchronization, however, or even the presence of a significant peristimulus response. In summary, the therapeutic effects of GPiDBS may be mediated by an abolition of low-frequency synchronized oscillations as a result of phasic driving.

We investigated the origin of spike frequency adaptation within a layered sensory network: the auditory pathway of locusts. Spike frequency adaptation as observed in an individual neuron may arise because of intrinsic or presynaptic adaptation mechanisms. To separate the contribution of different mechanisms, we recorded from the same cell during acoustic and intracellular current stimulation. We studied three identified neuron types that are representative for each network layer and participate in processing auditory patterns and localizing sound sources. By comparing current and acoustic stimulation, three distinct patterns of the distribution of adaptation mechanisms within the sensory network emerged: (1) balanced influence of both intrinsic and presynaptic adaptation mechanisms in an interneuron that summates over several receptor afferents (TN1), (2) predominantly inhibiting input as the source for spike frequency adaptation in a cell that transmits both pattern representation and directional information (BSN1), (3) primarily intrinsic, spike-triggered adaptation currents within an interneuron coding exclusively for direction (AN2). The time courses of spike frequency adaptation differed significantly between the cells types. Using the adaptation time constants, we were able to predict signal transmission properties for the different cells. We conclude that the adaptation mechanisms differ greatly among interneurons within this sensory pathway and are a function of their role in information processing.

An organism's ability to detect and discriminate sensory inputs depends on the recent stimulus history. For example, perceptual detection thresholds for a brief tone can be elevated by as much as 50 dB when following a masking stimulus. Previous work suggests that such forward masking is not a direct result of peripheral neural adaptation; the central pathway apparently modifies the representation in a way that further attenuates the input's response to short probe signals. Here, we show that much of this transformation is complete by the level of the inferior colliculus (IC). Single-neuron extracellular responses were recorded in the central nucleus of the awake marmoset IC. The threshold for a 20 ms probe tone presented at best frequency was determined for various masker-probe delays, over a range of masker sound pressure levels (SPLs) and frequencies. The most striking aspect of the data was the increased potency of forward maskers as their SPL was increased, despite the fact that the excitatory response to the masker was often saturating or nonmonotonic over the same range of levels. This led to probe thresholds at high masker levels that were almost always higher than those observed in the auditory nerve. Probe threshold shifts were not usually caused by a persistent excitatory response to the masker; instead we propose a wide-dynamic-range inhibitory mechanism locked to sound offset as an explanation for several key aspects of the data. These findings further delineate the role of subcortical auditory processing in the generation of a context-dependent representation of ongoing acoustic scenes.

Electrical activity in the brain spans a wide range of spatial and temporal scales, requiring simultaneous recording of multiple modalities of neurophysiological signals in order to capture various aspects of brain state dynamics. Here, we present a 16-channel neural interface integrated circuit fabricated in a 0.5 mum 3M2P CMOS process for selective digital acquisition of biopotentials across the spectrum of neural signal modalities in the brain, ranging from single spike action potentials to local field potentials (LFP), electrocorticograms (ECoG), and electroencephalograms (EEG). Each channel is composed of a tunable bandwidth, fixed gain front-end amplifier and a programmable gain/resolution continuous-time incremental DeltaSigma analog-to-digital converter (ADC). A two-stage topology for the front-end voltage amplifier with capacitive feedback offers independent tuning of the amplifier bandpass frequency corners, and attains a noise efficiency factor (NEF) of 2.9 at 8.2 kHz bandwidth for spike recording, and a NEF of 3.2 at 140 Hz bandwidth for EEG recording. The amplifier has a measured midband gain of 39.6 dB, frequency response from 0.2 Hz to 8.2 kHz, and an input-referred noise of 1.94 muV rms while drawing 12.2 muA of current from a 3.3 V supply. The lower and higher cutoff frequencies of the bandpass filter are adjustable from 0.2 to 94 Hz and 140 Hz to 8.2 kHz, respectively. At 10-bit resolution, the ADC has an SNDR of 56 dB while consuming 76 muW power. Time-modulation feedback in the ADC offers programmable digital gain (1-4096) for auto-ranging, further improving the dynamic range and linearity of the ADC. Experimental recordings with the system show spike signals in rat somatosensory cortex as well as alpha EEG activity in a human subject.

Background Magnetoencephalography (MEG) has become an increasingly popular technique for non-invasively characterizing neuromagnetic field changes in the brain at a high temporal resolution. To examine the reliability of the MEG signal, we compared magnetic and electrophysiological responses to complex natural stimuli from the same animals. We examined changes in neuromagnetic fields, local field potentials (LFP) and multi-unit activity (MUA) in macaque monkey primary somatosensory cortex that were induced by varying the rate of mechanical stimulation. Stimuli were applied to the fingertips with three inter-stimulus intervals (ISIs): 0.33s, 1s and 2s. Results Signal intensity was inversely related to the rate of stimulation, but to different degrees for each measurement method. The decrease in response at higher stimulation rates was significantly greater for MUA than LFP and MEG data, while no significant difference was observed between LFP and MEG recordings. Furthermore, response latency was the shortest for MUA and the longest for MEG data. Conclusion The MEG signal is an accurate representation of electrophysiological responses to complex natural stimuli. Further, the intensity and latency of the MEG signal were better correlated with the LFP than MUA data suggesting that the MEG signal reflects primarily synaptic currents rather than spiking activity. These differences in latency could be attributed to differences in the extent of spatial summation and/or differential laminar sensitivity.

When an object is introduced moving in the visual field of view, the object maps with different delays in each of the six cortical layers in many visual areas by mechanisms that are poorly understood. We combined voltage sensitive dye (VSD) recordings with laminar recordings of action potentials in visual areas 17, 18, 19 and 21 in ferrets exposed to stationary and moving bars. At the area 17/18 border a moving bar first elicited an ON response in layer 4 and then ON responses in supragranular and infragranular layers, identical to a stationary bar. Shortly after, the moving bar mapped as moving synchronous peak firing across layers. Complex dynamics evolved including feedback from areas 19/21, the computation of a spatially restricted pre-depolarization (SRP), and firing in the direction of cortical motion prior to the mapping of the bar. After 350 ms, the representations of the bar (peak firing and peak VSD signal) in areas 19/21 and 17/18 moved over the cortex in phase. The dynamics comprise putative mechanisms for automatic saliency of novel moving objects, coherent mapping of moving objects across layers and areas, and planning of catch-up saccades.

Commercially available data acquisition systems for multielectrode recording from freely moving animals are expensive, often rely on proprietary software, and do not provide detailed, modifiable circuit schematics. When used in conjunction with electrical stimulation, they are prone to prolonged, saturating stimulation artifacts that prevent the recording of short-latency evoked responses. Yet electrical stimulation is integral to many experimental designs, and critical for emerging brain-computer interfacing and neuroprosthetic applications. To address these issues, we developed an easy-to-use, modifiable, and inexpensive system for multielectrode neural recording and stimulation. Setup costs are less than US$10,000 for 64 channels, an order of magnitude lower than comparable commercial systems. Unlike commercial equipment, the system recovers rapidly from stimulation and allows short-latency action potentials (<1 ms post-stimulus) to be detected, facilitating closed-loop applications and exposing neural activity that would otherwise remain hidden. To illustrate this capability, evoked activity from microstimulation of the rodent hippocampus is presented. System noise levels are similar to existing platforms, and extracellular action potentials and local field potentials can be recorded simultaneously. The system is modular, in banks of 16 channels, and flexible in usage: while primarily designed for in vivo use, it can be combined with commercial preamplifiers to record from in vitro multielectrode arrays. The system's open-source control software, NeuroRighter, is implemented in C#, with an easy-to-use graphical interface. As C# functions in a managed code environment, which may impact performance, analysis was conducted to ensure comparable speed to C++ for this application. Hardware schematics, layout files, and software are freely available. Since maintaining wired headstage connections with freely moving animals is difficult, we describe a new method of electrode-headstage coupling using neodymium magnets.

The Python programming language is steadily increasing in popularity as the language of choice for scientific computing. The ability of this scripting environment to access a huge code base in various languages, combined with its syntactical simplicity, make it the ideal tool for implementing and sharing ideas among scientists from numerous fields and with heterogeneous methodological backgrounds. The recent rise of reciprocal interest between the machine learning (ML) and neuroscience communities is an example of the desire for an inter-disciplinary transfer of computational methods that can benefit from a Python-based framework. For many years, a large fraction of both research communities have addressed, almost independently, very high-dimensional problems with almost completely non-overlapping methods. However, a number of recently published studies that applied ML methods to neuroscience research questions attracted a lot of attention from researchers from both fields, as well as the general public, and showed that this approach can provide novel and fruitful insights into the functioning of the brain. In this article we show how PyMVPA, a specialized Python framework for machine learning based data analysis, can help to facilitate this inter-disciplinary technology transfer by providing a single interface to a wide array of machine learning libraries and neural data-processing methods. We demonstrate the general applicability and power of PyMVPA via analyses of a number of neural data modalities, including fMRI, EEG, MEG, and extracellular recordings.

Most sensory stimuli do not reach conscious perception during sleep. It has been thought that the thalamus prevents the relay of sensory information to cortex during sleep, but the consequences for cortical responses to sensory signals in this physiological state remain unclear. We recorded from two auditory cortical areas downstream of the thalamus in naturally sleeping marmoset monkeys. Single neurons in primary auditory cortex either increased or decreased their responses during sleep compared with wakefulness. In lateral belt, a secondary auditory cortical area, the response modulation was also bidirectional and showed no clear systematic depressive effect of sleep. When averaged across neurons, sound-evoked activity in these two auditory cortical areas was surprisingly well preserved during sleep. Neural responses to acoustic stimulation were present during both slow-wave and rapid-eye movement sleep, were repeatedly observed over multiple sleep cycles, and demonstrated similar discharge patterns to the responses recorded during wakefulness in the same neuron. Our results suggest that the thalamus is not as effective a gate for the flow of sensory information as previously thought. At the cortical stage, a novel pattern of activation/deactivation appears across neurons. Because the neural signal reaches as far as secondary auditory cortex, this leaves open the possibility of altered sensory processing of auditory information during sleep.

The directionality of hair cell stimulation combined with the vibration of the basilar membrane causes the auditory nerve fiber action potentials, in response to low-frequency stimuli, to occur at a particular phase of the stimulus waveform. Because direct mechanical measurements at the cochlear apex are difficult, such phase locking has often been used to indirectly infer the basilar membrane motion. Here, we confirm and extend earlier data from mammals using sine wave stimulation over a wide range of sound levels (up to 90 dB sound pressure level). We recorded phase-locked responses to pure tones over a wide range of frequencies and sound levels of a large population of auditory nerve fibers in the anesthetized guinea pig. The results indicate that, for a constant frequency of stimulation, the phase lag decreases with increases in the characteristic frequency (CF) of the nerve fiber. The phase lag decreases up to a CF above the stimulation frequency, beyond which it decreases at a much slower rate. Such phase changes are consistent with known basal cochlear mechanics. Measurements from individual fibers showed smaller but systematic variations in phase with sound level, confirming previous reports. We found a "null" stimulation frequency at which little variation in phase occurred with sound level. This null frequency was often not at the CF. At stimulation frequencies below the null, there was a progressive lag with sound level and a progressive lead for stimulation frequencies above the null. This was maximally 0.2 cycles.

Humans perceive a harmonic series as a single auditory object with a pitch equivalent to the fundamental frequency (F0) of the series. When harmonics are presented to alternate ears, the repetition rate of the waveform at each ear doubles. If the harmonics are resolved, then the pitch perceived is still equivalent to F0, suggesting the stimulus is binaurally integrated before pitch is processed. However, unresolved harmonics give rise to the doubling of pitch which would be expected from monaural processing (Bernstein and Oxenham, J. Acoust. Soc. Am., 113:3323-3334, 2003). We used similar stimuli to record responses of multi-unit clusters in the central nucleus of the inferior colliculus (IC) of anesthetized guinea pigs (urethane supplemented by fentanyl/fluanisone) to determine the nature of the representation of harmonic stimuli and to what extent there was binaural integration. We examined both the temporal and rate-tuning of IC clusters and found no evidence for binaural integration. Stimuli comprised all harmonics below 10 kHz with fundamental frequencies (F0) from 50 to 400 Hz in half-octave steps. In diotic conditions, all the harmonics were presented to both ears. In dichotic conditions, odd harmonics were presented to one ear and even harmonics to the other. Neural characteristic frequencies (CF, n = 85) were from 0.2 to 14.7 kHz; 29 had CFs below 1 kHz. The majority of clusters responded predominantly to the contralateral ear, with the dominance of the contralateral ear increasing with CF. With diotic stimuli, over half of the clusters (58%) had peaked firing rate vs. F0 functions. The most common peak F0 was 141 Hz. Almost all (98%) clusters phase locked diotically to an F0 of 50 Hz, and approximately 40% of clusters still phase locked significantly (Rayleigh coefficient >13.8) at the highest F0 tested (400 Hz). These results are consistent with the previous reports of responses to amplitude-modulated stimuli. Clusters phase locked significantly at a frequency equal to F0 for contralateral and diotic stimuli but at 2F0 for dichotic stimuli. We interpret these data as responses following the envelope periodicity in monaural channels rather than as a binaurally integrated representation.

This thesis is divided into six chapters (following Introduction). Each chapter was intended to be self-contained, so they do not have to be read in the order they are presented. Second chapter (Sec. 2) contains a detailed description of experimental techniques: surgery, recording, and training techniques we used in awake head-fixed rats. We have also included a detailed description of all sets of stimuli we used to probe neurons, analytical methods used to analyze data, and description of computational models used in other parts of the thesis.Third chapter (Sec. 3) focuses on description of single-neuron responses in primary auditory cortex of awake head-fixed rats. The primary emphasis of this part is on the sparse representation of various auditory stimuli we used to probe neurons, and the heterogeneity of responses of single neurons. To characterize population responses to sound in the auditory cortex we asked the question "What is the typical response to acoustic stimuli?" instead of what is usually asked "What is the stimulus that evokes a response?" We found that the population response was sparse, with many unresponsive neurons. In addition, the responsive neurons showed a great variety of responses. This heterogeneity of neuronal responses ("response zoo," courtesy of Anthony M. Zádor) was, however, surprisingly well characterized by lognormal distribution of firing rates. The observation that firing rates in awake auditory cortex were lognormally distributed was even more interesting given the observation of lognormal distribution of synaptic weights in the cerebral cortex.The fourth chapter (Sec. 4) focuses on mechanisms which could give rise to lognormal distribution of firing rates, as well as synaptic weights. We proposed specific types of correlations among synaptic connections, and formulated a multiplicative learning rule which led to the observed distributions. We were also able to characterize intracellular activity of neurons in awake auditory cortex. The fifth chapter (Sec. 5) contains analysis of so-called up and down states in awake auditory cortex. We show that up and down states—the "signature" subthreshold dynamics so often described in various cortical areas of anesthetized animals—were rare in the primary auditory cortex of awake rats, instead, subthreshold dynamics was consisted of brief, infrequent fluctuations of membrane potential.The experiments described and analyzed in chapters 2—-4 were conducted in naïve awake rats. As behavior or attention can influence neuronal activity even in primary sensory areas, we developed a setup for head-fixed behavior. In the sixth chapter (Sec. 6) we describe the sound discrimination task we have used to study behavior in head-fixed rats. We present a comparison of basic behavioral parameters between restrained and unrestrained rats, as well as evidence of nonauditory modulations of single neuron activity in auditory cortex.

Single-unit responses to infinitely iterated rippled noise and wideband noise were recorded from the cochlear nucleus of anesthetized chinchillas. Rippled noises had a fixed delay of 4ms, and spectral depth was varied by attenuating the delayed version of the noise. Temporal discharge patterns were analyzed using neural autocorrelograms, and responses to rippled noises were compared to wideband noise responses. Chopper units with best frequencies in the range of the first to second harmonics of the rippled noise showed large differences in discharge patterns between rippled noise and wideband noise responses, but chopper units with best frequencies centered at higher harmonics did not show large differences. Consequently, the Chopper group of units showed no evidence of a neural representation of the dominance region. Primarylike units did show a neural representation of dominance that is related to behavioral performance. For Primarylike units with best frequencies around the third to fifth harmonics of the rippled noise, large differences in discharge patterns between rippled noise and wideband noise responses were observed. The results suggest that bushy cells play an important role in processing pitch-related information and should be included as important elements in neural models of periodicity processing.

A new subthreshold form of multisensory processing has been recently identified that results from the convergence of suprathreshold excitatory inputs from one modality with subthreshold inputs from another. Because of the subthreshold nature of the second modality, descriptive measures of sensory features such as receptive field properties or location are not directly apparent as they are for traditional bimodal neurons. This raises the question of whether or not subthreshold signals actually convey sensory-specific receptive field information as seen in their bimodal counterparts, or if they represent non-specific effects such as arousal. The present experiment addressed this issue in visually-responsive neurons from the cat posterolateral lateral suprasylvian cortex (PLLS). Single-unit electrophysiological techniques were used to record neuronal responses to visual, auditory and combined visual-auditory stimuli while the intensity of stimulation in the subthreshold auditory modality was systematically altered. The results showed that subthreshold multisensory neurons were sensitive to changes in auditory stimulus intensity. These receptive field sensitivities are similar to those observed in bimodal neurons and thereby represent sensory-specific, not arousal-related responses. In addition, these results provide further support for the notion that multisensory processing occurs along a dynamic continuum of neuronal convergence patterns from bimodal to purely sensory-specific.

Despite their prevalence in nature, echoes are not perceived as events separate from the sounds arriving directly from an active source, until the echo's delay is long. We measured the head-saccades of barn owls and the responses of neurons in their auditory space-maps while presenting a long duration noise-burst and a simulated echo. Under this paradigm, there were two possible stimulus segments that could potentially signal the location of the echo. One was at the onset of the echo; the other, after the offset of the direct (leading) sound, when only the echo was present. By lengthening the echo's duration, independently of its delay, spikes and saccades were evoked by the source of the echo even at delays that normally evoked saccades to only the direct source. An echo's location thus appears to be signaled by the neural response evoked after the offset of the direct sound.

On the basis of its primary circuit it has been postulated that the olfactory bulb (OB) is analogous to the retina in mammals. In retina, repeated exposure to the same visual stimulus results in a neural representation that remains relatively stable over time, even as the meaning of that stimulus to the animal changes. Stability of stimulus representation at early stages of processing allows for unbiased interpretation of incoming stimuli by higher order cortical centers. The alternative is that early stimulus representation is shaped by previously derived meaning, which could allow more efficient sampling of odor space providing a simplified yet biased interpretation of incoming stimuli. This study helps place the olfactory system on this continuum of subjective versus objective early sensory representation. Here we show that odor responses of the output cells of the OB, mitral cells, change transiently during a go-no-go odor discrimination task. The response changes occur in a manner that increases the ability of the circuit to convey information necessary to discriminate among closely related odors. Remarkably, a switch between which of the two odors is rewarded causes mitral cells to switch the polarity of their divergent responses. Taken together these results redefine the function of the OB as a transiently modifiable (active) filter, shaping early odor representations in behaviorally meaningful ways.

The medial nucleus of the trapezoid body (MNTB) receives excitatory input from giant presynaptic terminals, the calyces of Held. The MNTB functions as a sign inverter giving inhibitory input to the lateral and medial superior olive, where its input is important in the generation of binaural sensitivity to cues for sound localization. Extracellular recordings from MNTB neurons show complex spikes consisting of a prepotential, thought to reflect synaptic activation, followed by a postsynaptic action potential. This makes the synapse ideal to study synaptic transmission in vivo because presynaptic and postsynaptic activity can be monitored with a single electrode. Recent in vivo and in vitro studies have observed isolated prepotentials in the MNTB suggesting that, under certain stimulus conditions, synaptic transmission fails. We investigated synaptic transmission at the calyx of Held in the MNTB of the adult cat and concluded that synaptic transmission was completely secure in terms of rate of transmitted spikes. However, synaptic transmission was found to be less secure in terms of timing. With increasing spike rate, the synaptic delay showed an increase of up to 100 μs, as well as a decrease in amplitude of the action potential. This variability in delay is of a surprisingly high magnitude given the hypothesized role of these binaural circuits in sound localization and given the fact that this is one of the largest synapses in the mammalian brain.

The influence of noise exposure on the parameters of a convolution model of the compound action potential (CAP) was examined. CAPs were recorded in normal-hearing gerbils and in gerbils exposed to a 117dBSPL 8kHz band of noise for various durations. The CAPs were fitted with an analytic CAP to obtain the parameters representing the number of nerve fibers (N), the probability density function [P(t)] from a population of nerve fibers, and the single-unit waveform [U(t)]. The results showed that the analytic CAP fitted the physiologic CAPs well with correlations of approximately 0.90. A subsequent analysis using hierarchical linear modeling quantified the change in the parameters as a function of both signal level and hearing threshold. The results showed that noise exposure caused some of the parameter-level functions to simply shift along the signal level axis in proportion to the amount of hearing loss, whereas others shifted along the signal level axis and steepened. Significant changes occurred in the U(t) parameters, but they were not related to hearing threshold. These results suggest that noise exposure alters the physiology underlying the CAP, some of which can be explained by a simple lack of gain, whereas others may not.