Entropy analysis of neuronal spike train synchrony

Spike Spectra for Recurrences

In recurrence analysis, the τ-recurrence rate encodes the periods of the cycles of the underlying high-dimensional time series. It, thus, plays a similar role to the autocorrelation for scalar time-series in encoding temporal correlations. However, its Fourier decomposition does not have a clean interpretation. Thus, there is no satisfactory analogue to the power spectrum in recurrence analysis. We introduce a novel method to decompose the τ-recurrence rate using an over-complete basis of Dirac combs together with sparsity regularization. We show that this decomposition, the inter-spike spectrum, naturally provides an analogue to the power spectrum for recurrence analysis in the sense that it reveals the dominant periodicities of the underlying time series. We show that the inter-spike spectrum correctly identifies patterns and transitions in the underlying system in a wide variety of examples and is robust to measurement noise.

Neural Mechanisms Underlying High-Frequency Vestibulocollic Reflexes In Humans And Monkeys

The vestibulocollic reflex is a compensatory response that stabilizes the head in space. During everyday activities, this stabilizing response is evoked by head movements that typically span frequencies from 0 to 30 Hz. Transient head impacts, however, can elicit head movements with frequency content up to 300-400 Hz, raising the question whether vestibular pathways contribute to head stabilization at such high frequencies. Here, we first established that electrical vestibular stimulation modulates human neck motor unit (MU) activity at sinusoidal frequencies up to 300 Hz, but that sensitivity increases with frequency up to a low-pass cutoff of ∼70-80 Hz. To examine the neural substrates underlying the low-pass dynamics of vestibulocollic reflexes, we then recorded vestibular afferent responses to the same electrical stimuli in monkeys. Vestibular afferents also responded to electrical stimuli up to 300 Hz, but in contrast to MUs their sensitivity increased with frequency up to the afferent resting firing rate (∼100-150 Hz) and at higher frequencies afferents tended to phase-lock to the vestibular stimulus. This latter nonlinearity, however, was not transmitted to neck motoneurons, which instead showed minimal phase-locking that decreased at frequencies >75 Hz. Similar to human data, we validated that monkey muscle activity also exhibited low-pass filtered vestibulocollic reflex dynamics. Together, our results show that neck MUs are activated by high-frequency signals encoded by primary vestibular afferents, but undergo low-pass filtering at intermediate stages in the vestibulocollic reflex. These high-frequency contributions to vestibular-evoked neck muscle responses could stabilize the head during unexpected head transients.SIGNIFICANCE STATEMENT Vestibular-evoked neck muscle responses rely on accurate encoding and transmission of head movement information to stabilize the head in space. Unexpected transient events, such as head impacts, are likely to push the limits of these neural pathways since their high-frequency features (0-300 Hz) extend beyond the frequency bandwidth of head movements experienced during everyday activities (0-30 Hz). Here, we demonstrate that vestibular primary afferents encode high-frequency stimuli through frequency-dependent increases in sensitivity and phase-locking. When transmitted to neck motoneurons, these signals undergo low-pass filtering that limits neck motoneuron phase-locking in response to stimuli >75 Hz. This study provides insight into the neural dynamics producing vestibulocollic reflexes, which may respond to high-frequency transient events to stabilize the head.

Soleus single motor units show stronger coherence with Achilles tendon vibration across a broad bandwidth relative to medial gastrocnemius units while standing

To probe the frequency characteristics of somatosensory responses in the triceps surae muscles, we previously applied suprathreshold noisy vibration to the Achilles tendon and correlated it with ongoing triceps surae muscle activity (recorded via surface EMG) during standing. Stronger responses to tendon stimuli were observed in soleus (Sol) relative to medial gastrocnemius (MGas) surface EMG; however, it is unknown whether differences in motor unit activity or limitations of surface EMG could have influenced this finding. Here, we inserted indwelling EMG into Sol and MGas to record the activity of single motor units while we applied noisy vibration (10-115 Hz) to the right Achilles tendon of standing participants. We analyzed the relationship between vibration acceleration and the spike activity of active single motor units through estimates of coherence, gain, phase, and cross-covariance. We also applied sinusoidal vibration at frequencies from 10 to 100 Hz (in 5-Hz increments) to examine whether motor units demonstrate nonlinear synchronization or phase locking at higher frequencies. Relative to MGas single motor units, Sol units demonstrated stronger coherence and higher gain with noisy vibration across a bandwidth of 7-68 Hz, and larger peak-to-peak cross-covariance at all four stimulus amplitudes examined. Sol and MGas motor unit activity was modulated over the time course of the sinusoidal stimuli across all frequencies, but their phase-locking behavior was minimal. These findings suggest Sol plays a prominent role in responding to disturbances transmitted through the Achilles tendon across a broad frequency band during standing.NEW & NOTEWORTHY We examined the relationship between Achilles tendon stimuli and spike times of single soleus (Sol) and medial gastrocnemius (MGas) motor units during standing. Relative to MGas, Sol units demonstrated stronger coherence and higher gain with noisy stimuli across a bandwidth of 7-68 Hz. Sol and MGas units demonstrated minimal nonlinear phase locking with sinusoidal stimuli. These findings indicate Sol plays a prominent role in responding to tendon stimuli across a broad frequency band.

Coding strategies in the otolith system differ for translational head motion vs. static orientation relative to gravity

The detection of gravito-inertial forces by the otolith system is essential for our sense of balance and accurate perception. To date, however, how this system encodes the self-motion stimuli that are experienced during everyday activities remains unknown. Here, we addressed this fundamental question directly by recording from single otolith afferents in monkeys during naturalistic translational self-motion and changes in static head orientation. Otolith afferents with higher intrinsic variability transmitted more information overall about translational self-motion than their regular counterparts, owing to stronger nonlinearities that enabled precise spike timing including phase locking. By contrast, more regular afferents better discriminated between different static head orientations relative to gravity. Using computational methods, we further demonstrated that coupled increases in intrinsic variability and sensitivity accounted for the observed functional differences between afferent classes. Together, our results indicate that irregular and regular otolith afferents use different strategies to encode naturalistic self-motion and static head orientation relative to gravity.

Calcium Activity Dynamics Correlate with Neuronal Phenotype at a Single Cell Level and in a Threshold-Dependent Manner

Calcium is a ubiquitous signaling molecule that plays a vital role in many physiological processes. Recent work has shown that calcium activity is especially critical in vertebrate neural development. Here, we investigated if calcium activity and neuronal phenotype are correlated only on a population level or on the level of single cells. Using Xenopus primary cell culture in which individual cells can be unambiguously identified and associated with a molecular phenotype, we correlated calcium activity with neuronal phenotype on the single-cell level. This analysis revealed that, at the neural plate stage, a high frequency of low-amplitude spiking activity correlates with an excitatory, glutamatergic phenotype, while high-amplitude spiking activity correlates with an inhibitory, GABAergic phenotype. Surprisingly, we also found that high-frequency, low-amplitude spiking activity correlates with neural progenitor cells and that differentiating cells exhibit higher spike amplitude. Additional methods of analysis suggested that differentiating marker tubb2b-expressing cells exhibit relatively persistent and predictable calcium activity compared to the irregular activity of neural progenitor cells. Our study highlights the value of using a range of thresholds for analyzing calcium activity data and underscores the importance of employing multiple methods to characterize the often irregular, complex patterns of calcium activity during early neural development.

Ergodicity and parameter estimates in auditory neural circuits

This paper discusses ergodic properties and circular statistical characteristics in neuronal spike trains. Ergodicity means that the average taken over a long time period and over smaller population should equal the average in less time and larger population. The objectives are to show simple examples of design and validation of a neuronal model, where the ergodicity assumption helps find correspondence between variables and parameters. The methods used are analytical and numerical computations, numerical models of phenomenological spiking neurons and neuronal circuits. Results obtained using these methods are the following. They are: a formula to calculate vector strength of neural spike timing dependent on the spike train parameters, description of parameters of spike train variability and model of output spiking density based on assumption of the computation realized by sound localization neural circuit. Theoretical results are illustrated by references to experimental data. Examples of neurons where spike trains have and do not have the ergodic property are then discussed.

Locomotor corollary activation of trigeminal motoneurons: coupling of discrete motor behaviors

During motor behavior, corollary discharges of the underlying motor commands inform sensory-motor systems about impending or ongoing movements. These signals generally limit the impact of self-generated sensory stimuli but also induce motor reactions that stabilize sensory perception. Here, we demonstrate in isolated preparations of Xenopus laevis tadpoles that locomotor corollary discharge provokes a retraction of the mechanoreceptive tentacles during fictive swimming. In the absence of sensory feedback, these signals activate a cluster of trigeminal motoneurons that cause a contraction of the tentacle muscle. This corollary discharge encodes duration and strength of locomotor activity, thereby ensuring a reliable coupling between locomotion and tentacle motion. The strict phase coupling between the trigeminal and spinal motor activity, present in many cases, suggests that the respective corollary discharge is causally related to the ongoing locomotor output and derives at least in part from the spinal central pattern generator; however, additional contributions from midbrain and/or hindbrain locomotor centers are likely. The swimming-related retraction might protect the touch-receptive Merkel cells on the tentacle from sensory over-stimulation and damage and/or reduce the hydrodynamic drag. The intrinsic nature of the coupling of tentacle retraction to locomotion is an excellent example of a context-dependent, direct link between otherwise discrete motor behaviors.

Parallel sparse and dense information coding streams in the electrosensory midbrain

Efficient processing of incoming sensory information is critical for an organism's survival. It has been widely observed across systems and species that the representation of sensory information changes across successive brain areas. Indeed, peripheral sensory neurons tend to respond densely to a broad range of sensory stimuli while more central neurons tend to instead respond sparsely to a narrow range of stimuli. Such a transition might be advantageous as sparse neural codes are thought to be metabolically efficient and optimize coding efficiency. Here we investigated whether the neural code transitions from dense to sparse within the midbrain Torus semicircularis (TS) of weakly electric fish. Confirming previous results, we found both dense and sparse coding neurons. However, subsequent histological classification revealed that most dense neurons projected to higher brain areas. Our results thus provide strong evidence against the hypothesis that the neural code transitions from dense to sparse in the electrosensory system. Rather, they support the alternative hypothesis that higher brain areas receive parallel streams of dense and sparse coded information from the electrosensory midbrain. We discuss the implications and possible advantages of such a coding strategy and argue that it is a general feature of sensory processing.

Vector strength after Goldberg, Brown, and von Mises: biological and mathematical perspectives

The vector strength, a number between 0 and 1, is a classical notion in biology. It was first used in neurobiology by Goldberg and Brown (J Neurophys 31:639-656, 1969) but dates back at least to von Mises (Phys Z 19:490-500, 1918). It is widely used as a means to measure the periodicity or lack of periodicity of a neuronal response to an outside periodic signal. Here, we provide a self-contained and simple treatment of a closely related notion, the synchrony vector, a complex number with the vector strength as its absolute value and with a definite phase that one can directly relate to a biophysical delay. The present analysis is essentially geometrical and based on convexity. As such it does two things. First, it maps a sequence of points, events such as spike times on the time axis, onto the unit circle in the complex plane so that for a perfectly periodic repetition, a single point on the unit circle appears. Second, events hardly ever occur periodically, so that we need a criterion of how to extract periodicity out of a set of real numbers. It is here where convex geometry comes in, and a geometrically intuitive picture results. We also quantify how the events cluster around a period as the vector strength goes to 1. A typical example from the auditory system is used to illustrate the general considerations. Furthermore, von Mises' seminal contribution to the notion of vector strength is explained in detail. Finally, we generalize the synchrony vector to a function of angular frequency, not fixed on the input frequency at hand and indicate its potential as a "resonating" vector strength.

Active engagement improves primary auditory cortical neurons' ability to discriminate temporal modulation

The effect of attention on single neuron responses in the auditory system is unresolved. We found that when monkeys discriminated temporally amplitude modulated (AM) from unmodulated sounds, primary auditory cortical (A1) neurons better discriminated those sounds than when the monkeys were not discriminating them. This was observed for both average firing rate and vector strength (VS), a measure of how well neurons temporally follow the stimulus' temporal modulation. When data were separated by nonsynchronized and synchronized responses, the firing rate of nonsynchronized responses best distinguished AM- noise from unmodulated noise, followed by VS for synchronized responses, with firing rate for synchronized neurons providing the poorest AM discrimination. Firing rate-based AM discrimination for synchronized neurons, however, improved most with task engagement, showing that the least sensitive code in the passive condition improves the most with task engagement. Rate coding improved due to larger increases in absolute firing rate at higher modulation depths than for lower depths and unmodulated sounds. Relative to spontaneous activity (which increased with engagement), the response to unmodulated sounds decreased substantially. The temporal coding improvement--responses more precisely temporally following a stimulus when animals were required to attend to it--expands the framework of possible mechanisms of attention to include increasing temporal precision of stimulus following. These findings provide a crucial step to understanding the coding of temporal modulation and support a model in which rate and temporal coding work in parallel, permitting a multiplexed code for temporal modulation, and for a complementary representation of rate and temporal coding.

Ability of primary auditory cortical neurons to detect amplitude modulation with rate and temporal codes: neurometric analysis

Amplitude modulation (AM) is a common feature of natural sounds, and its detection is biologically important. Even though most sounds are not fully modulated, the majority of physiological studies have focused on fully modulated (100% modulation depth) sounds. We presented AM noise at a range of modulation depths to awake macaque monkeys while recording from neurons in primary auditory cortex (A1). The ability of neurons to detect partial AM with rate and temporal codes was assessed with signal detection methods. On average, single-cell synchrony was as or more sensitive than spike count in modulation detection. Cells are less sensitive to modulation depth if tested away from their best modulation frequency, particularly for temporal measures. Mean neural modulation detection thresholds in A1 are not as sensitive as behavioral thresholds, but with phase locking the most sensitive neurons are more sensitive, suggesting that for temporal measures the lower-envelope principle cannot account for thresholds. Three methods of preanalysis pooling of spike trains (multiunit, similar to convergence from a cortical column; within cell, similar to convergence of cells with matched response properties; across cell, similar to indiscriminate convergence of cells) all result in an increase in neural sensitivity to modulation depth for both temporal and rate codes. For the across-cell method, pooling of a few dozen cells can result in detection thresholds that approximate those of the behaving animal. With synchrony measures, indiscriminate pooling results in sensitive detection of modulation frequencies between 20 and 60 Hz, suggesting that differences in AM response phase are minor in A1.

Testing resonating vector strength: auditory system, electric fish, and noise

Quite often a response to some input with a specific frequency ν(○) can be described through a sequence of discrete events. Here, we study the synchrony vector, whose length stands for the vector strength, and in doing so focus on neuronal response in terms of spike times. The latter are supposed to be given by experiment. Instead of singling out the stimulus frequency ν(○) we study the synchrony vector as a function of the real frequency variable ν. Its length turns out to be a resonating vector strength in that it shows clear maxima in the neighborhood of ν(○) and multiples thereof, hence, allowing an easy way of determining response frequencies. We study this "resonating" vector strength for two concrete but rather different cases, viz., a specific midbrain neuron in the auditory system of cat and a primary detector neuron belonging to the electric sense of the wave-type electric fish Apteronotus leptorhynchus. We show that the resonating vector strength always performs a clear resonance correlated with the phase locking that it quantifies. We analyze the influence of noise and demonstrate how well the resonance associated with maximal vector strength indicates the dominant stimulus frequency. Furthermore, we exhibit how one can obtain a specific phase associated with, for instance, a delay in auditory analysis.

Response properties of the electrosensory neurons in hindbrain of the white sturgeon, Acipenser transmontanus

OBJECTIVE

The passive electrosense is a primitive sensory modality in the Chondrostei, which include sturgeon and paddlefish. Using electroreceptors, these fish detect the weak electric fields from other animals or geoelectric sources, and use this information for prey detection or other behaviors. The primary afferent fibers innervating the electroreceptors project to a single hindbrain target called the dorsal octavolateral nucleus (DON), where the electrosensory information is first processed. Here, we investigated the electrophysiological properties of DON neurons.

METHODS

Extracellular recording was used to investigate the response properties of DON neurons to dipole electric fields with different amplitudes and frequencies in the white sturgeon, Acipenser transmontanus.

RESULTS

The DON neurons showed regular spontaneous activity and could be classified into two types: neurons with a low spontaneous rate (<10 Hz) and those with a high spontaneous rate (>10 Hz). In response to sinusoidal electric field stimuli, DON neurons showed sinusoidally-modulated and phase-locked firing. In addition, neurons showed opposite phase responses corresponding to the different directions of the dipole.

CONCLUSION

The response properties of DON neurons match the electrosensory biological function in sturgeon, as they match the characteristics of the electric fields of its prey.

Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish

While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.

In vivo conditions induce faithful encoding of stimuli by reducing nonlinear synchronization in vestibular sensory neurons

Previous studies have shown that neurons within the vestibular nuclei (VN) can faithfully encode the time course of sensory input through changes in firing rate in vivo. However, studies performed in vitro have shown that these same VN neurons often display nonlinear synchronization (i.e. phase locking) in their spiking activity to the local maxima of sensory input, thereby severely limiting their capacity for faithful encoding of said input through changes in firing rate. We investigated this apparent discrepancy by studying the effects of in vivo conditions on VN neuron activity in vitro using a simple, physiologically based, model of cellular dynamics. We found that membrane potential oscillations were evoked both in response to step and zap current injection for a wide range of channel conductance values. These oscillations gave rise to a resonance in the spiking activity that causes synchronization to sinusoidal current injection at frequencies below 25 Hz. We hypothesized that the apparent discrepancy between VN response dynamics measured in in vitro conditions (i.e., consistent with our modeling results) and the dynamics measured in vivo conditions could be explained by an increase in trial-to-trial variability under in vivo vs. in vitro conditions. Accordingly, we mimicked more physiologically realistic conditions in our model by introducing a noise current to match the levels of resting discharge variability seen in vivo as quantified by the coefficient of variation (CV). While low noise intensities corresponding to CV values in the range 0.04-0.24 only eliminated synchronization for low (<8 Hz) frequency stimulation but not high (>12 Hz) frequency stimulation, higher noise intensities corresponding to CV values in the range 0.5-0.7 almost completely eliminated synchronization for all frequencies. Our results thus predict that, under natural (i.e. in vivo) conditions, the vestibular system uses increased variability to promote fidelity of encoding by single neurons. This prediction can be tested experimentally in vitro.

Complex propagation patterns characterize human cortical activity during slow-wave sleep

Cortical electrical activity during nonrapid eye movement (non-REM) sleep is dominated by slow-wave activity (SWA). At larger spatial scales (∼2-30 cm), investigated by scalp EEG recordings, SWA has been shown to propagate globally over wide cortical regions as traveling waves, which has been proposed to serve as a temporal framework for neural plasticity. However, whether SWA dynamics at finer spatial scales also reflects the orderly propagation has not previously been investigated in humans. To reveal the local, finer spatial scale (∼1-6 cm) patterns of SWA propagation during non-REM sleep, electrocorticographic (ECoG) recordings were conducted from subdurally implanted electrode grids and a nonlinear correlation technique [mutual information (MI)] was implemented. MI analysis revealed spatial maps of correlations between cortical areas demonstrating SWA propagation directions, speed, and association strength. Highest correlations, indicating significant coupling, were detected during the initial positive-going deflection of slow waves. SWA propagated predominantly between adjacent cortical areas, albeit spatial noncontinuities were also frequently observed. MI analysis further uncovered significant convergence and divergence patterns. Areas receiving the most convergent activity were similar to those with high divergence rate, while reciprocal and circular propagation of SWA was also frequent. We hypothesize that SWA is characterized by distinct attributes depending on the spatial scale observed. At larger spatial scales, the orderly SWA propagation dominates; at the finer scale of the ECoG recordings, non-REM sleep is characterized by complex SWA propagation patterns.

Coding of amplitude modulation in primary auditory cortex

Conflicting results have led to different views about how temporal modulation is encoded in primary auditory cortex (A1). Some studies find a substantial population of neurons that change firing rate without synchronizing to temporal modulation, whereas other studies fail to see these nonsynchronized neurons. As a result, the role and scope of synchronized temporal and nonsynchronized rate codes in AM processing in A1 remains unresolved. We recorded A1 neurons' responses in awake macaques to sinusoidal AM noise. We find most (37-78%) neurons synchronize to at least one modulation frequency (MF) without exhibiting nonsynchronized responses. However, we find both exclusively nonsynchronized neurons (7-29%) and "mixed-mode" neurons (13-40%) that synchronize to at least one MF and fire nonsynchronously to at least one other. We introduce new measures for modulation encoding and temporal synchrony that can improve the analysis of how neurons encode temporal modulation. These include comparing AM responses to the responses to unmodulated sounds, and a vector strength measure that is suitable for single-trial analysis. Our data support a transformation from a temporally based population code of AM to a rate-based code as information ascends the auditory pathway. The number of mixed-mode neurons found in A1 indicates this transformation is not yet complete, and A1 neurons may carry multiplexed temporal and rate codes.

Information flow in the auditory cortical network

Auditory processing in the cerebral cortex is comprised of an interconnected network of auditory and auditory-related areas distributed throughout the forebrain. The nexus of auditory activity is located in temporal cortex among several specialized areas, or fields, that receive dense inputs from the medial geniculate complex. These areas are collectively referred to as auditory cortex. Auditory activity is extended beyond auditory cortex via connections with auditory-related areas elsewhere in the cortex. Within this network, information flows between areas to and from countless targets, but in a manner that is characterized by orderly regional, areal and laminar patterns. These patterns reflect some of the structural constraints that passively govern the flow of information at all levels of the network. In addition, the exchange of information within these circuits is dynamically regulated by intrinsic neurochemical properties of projecting neurons and their targets. This article begins with an overview of the principal circuits and how each is related to information flow along major axes of the network. The discussion then turns to a description of neurochemical gradients along these axes, highlighting recent work on glutamate transporters in the thalamocortical projections to auditory cortex. The article concludes with a brief discussion of relevant neurophysiological findings as they relate to structural gradients in the network.

GABAergic neurons of the medial septum lead the hippocampal network during theta activity

Information processing in the hippocampus critically relies on its reciprocal interaction with the medial septum (MS). Synchronization of the septo-hippocampal system was demonstrated during both major hippocampal activity states, the regular theta rhythm and the large amplitude irregular activity. Previous experimental and modeling data suggest that the MS provides rhythmic drive to the hippocampus, and hippocampo-septal feedback synchronizes septal pacemaker units. However, this view has recently been questioned based on the possibility of intrahippocampal theta genesis. Previously, we identified putative pacemaker neurons expressing parvalbumin (PV) and/or the pacemaker hyperpolarization-activated and cyclic nucleotide-gated nonselective cation channel (HCN) in the MS. In this study, by analyzing the temporal relationship of activity between the PV/HCN-containing medial septal neurons and hippocampal local field potential, we aimed to uncover whether the sequence of events during theta formation supports the classic view of septal drive or the challenging theory of hippocampal pacing of theta. Importantly, by implementing a circular statistical method, a temporal lead of these septal neurons over the hippocampus was observed on the course of theta synchronization. Moreover, the activity of putative hippocampal interneurons also preceded hippocampal local field theta, but by a shorter time period compared with PV/HCN-containing septal neurons. Using the concept of mutual information, the action potential series of PV/HCN-containing neurons shared higher amount of information with hippocampal field oscillation than PV/HCN-immunonegative cells. Thus, a pacemaker neuron population of the MS leads hippocampal activity, presumably via the synchronization of hippocampal interneurons.

Temporal processing across multiple topographic maps in the electrosensory system

Multiple topographic representations of sensory space are common in the nervous system and presumably allow organisms to separately process particular features of incoming sensory stimuli that vary widely in their attributes. We compared the response properties of sensory neurons within three maps of the body surface that are arranged strictly in parallel to two classes of stimuli that mimic prey and conspecifics, respectively. We used information-theoretic approaches and measures of phase locking to quantify neuronal responses. Our results show that frequency tuning in one of the three maps does not depend on stimulus class. This map acts as a low-pass filter under both conditions. A previously described stimulus-class-dependent switch in frequency tuning is shown to occur in the other two maps. Only a fraction of the information encoded by all neurons could be recovered through a linear decoder. Particularly striking were low-pass neurons the information of which in the high-frequency range could not be decoded linearly. We then explored whether intrinsic cellular mechanisms could partially account for the differences in frequency tuning across maps. Injection of a Ca2+ chelator had no effect in the map with low-pass characteristics. However, injection of the same Ca2+ chelator in the other two maps switched the tuning of neurons from band-pass/high-pass to low-pass. These results show that Ca2+-dependent processes play an important part in determining the functional roles of different sensory maps and thus shed light on the evolution of this important feature of the vertebrate brain.

Response properties of electrosensory units in the midbrain tectum of the paddlefish (Polyodon spathula Walbaum)

Paddlefish use their peculiar rostrum to detect minute electric fields from their main prey, small water fleas. Electroreceptors over the rostrum and head sense these fields and send the information into a single hindbrain area, the dorsal octavolateral nucleus (DON). From there, information is sent to various midbrain structures, including the tectum. The response properties of primary afferent fibers and DON units has been well investigated, but nothing is known about electrosensory units in the midbrain. Here we recorded the responses of single units in the midbrain tectum and DON to uniform electric fields. Tectal units exhibited little spontaneous activity and responded to sine waves with a few, well phase-locked spikes. Phase locking was still significant at amplitudes one order of magnitude lower than in the DON. If stimulated with sinusoidal electric fields of different frequencies, phase locking in DON units decreased proportionally with frequency whereas the response of tectal units depended little on frequency. This is in agreement with behavioral studies showing that relevant frequencies range from DC to ca 20 Hz.

Coding of FM sweep trains and twitter calls in area CM of marmoset auditory cortex

The primate auditory cortex contains three interconnected regions (core, belt, parabelt), which are further subdivided into discrete areas. The caudomedial area (CM) is one of about seven areas in the belt region that has been the subject of recent anatomical and physiological studies conducted to define the functional organization of auditory cortex. The main goal of the present study was to examine temporal coding in area CM of marmoset monkeys using two related classes of acoustic stimuli: (1) marmoset twitter calls; and (2) frequency-modulated (FM) sweep trains modeled after the twitter call. The FM sweep trains were presented at repetition rates between 1 and 24 Hz, overlapping the natural phrase frequency of the twitter call (6-8 Hz). Multiunit recordings in CM revealed robust phase-locked responses to twitter calls and FM sweep trains. For the latter, phase-locking quantified by vector strength (VS) was best at repetition rates between 2 and 8 Hz, with a mean of about 5 Hz. Temporal response patterns were not strictly phase-locked, but exhibited dynamic features that varied with the repetition rate. To examine these properties, classification of the repetition rate from the temporal response pattern evoked by twitter calls and FM sweep trains was examined by Fisher's linear discrimination analysis (LDA). Response classification by LDA revealed that information was encoded not only by phase-locking, but also other components of the temporal response pattern. For FM sweep trains, classification was best for repetition rates from 2 to 8 Hz. Thus, the majority of neurons in CM can accurately encode the envelopes of temporally complex stimuli over the behaviorally-relevant range of the twitter call. This suggests that CM could be engaged in processing that requires relatively precise temporal envelope discrimination, and supports the hypothesis that CM is positioned at an early stage of processing in the auditory cortex of primates.

Dynamic amplitude coding in the auditory cortex of awake rhesus macaques

In many animals, the information most important for processing communication sounds, including speech, consists of temporal envelope cues below approximately 20 Hz. Physiological studies, however, have typically emphasized the upper limits of modulation encoding. Responses to sinusoidal AM (SAM) are generally summarized by modulation transfer functions (MTFs), which emphasize tuning to modulation frequency rather than the representation of the instantaneous stimulus amplitude. Unfortunately, MTFs fail to capture important but nonlinear aspects of amplitude coding in the central auditory system. We focus on an alternative data representation, the modulation period histogram (MPH), which depicts the spike train folded on the modulation period of the SAM stimulus. At low modulation frequencies, the fluctuations of stimulus amplitude in decibels are robustly encoded by the cycle-by-cycle response dynamics evident in the MPH. We show that all of the parameters that define a SAM stimulus--carrier frequency, carrier level, modulation frequency, and modulation depth--are reflected in the shape of cortical MPHs. In many neurons that are nonmonotonically tuned for sound amplitude, the representation of modulation frequency is typically sacrificed to preserve the mapping between the instantaneous discharge rate and the instantaneous stimulus amplitude, resulting in two response modes per modulation cycle. This behavior, as well as the relatively poor tuning of cortical MTFs, suggests that auditory cortical neurons are not well suited for operating as a "modulation filterbank." Instead, our results suggest that <20 Hz, the processing of modulated signals is better described as envelope shape discrimination rather than modulation frequency extraction.

Cortical connections of the auditory cortex in marmoset monkeys: core and medial belt regions

The auditory cortex of primates contains a core region of three primary areas surrounded by a belt region of secondary areas. Recent neurophysiological studies suggest that the belt areas medial to the core have unique functional roles, including multisensory properties, but little is known about their connections. In this study and its companion, the cortical and subcortical connections of the core and medial belt regions of marmoset monkeys were compared to account for functional differences between areas and refine our working model of the primate auditory cortex. Anatomical tracer injections targeted two core areas (A1 and R) and two medial belt areas (rostromedial [RM] and caudomedial [CM]). RM and CM had topographically weighted connections with all other areas of the auditory cortex ipsilaterally, but these were less widespread contralaterally. CM was densely connected with caudal auditory fields, the retroinsular (Ri) area of the somatosensory cortex, the superior temporal sulcus (STS), and the posterior parietal and entorhinal cortex. The connections of RM favored rostral auditory areas, with no clear somatosensory inputs. RM also projected to the lateral nucleus of the amygdala and tail of the caudate nucleus. A1 and R had topographically weighted connections with medial and lateral belt regions, infragranular inputs from the parabelt, and weak connections with fields outside the auditory cortex. The results indicated that RM and CM are distinct areas of the medial belt region with direct inputs from the core. CM also has somatosensory input and may correspond to an area on the posteromedial transverse gyrus of humans and the anterior auditory field of other mammals.

Thalamic connections of the auditory cortex in marmoset monkeys: core and medial belt regions

In this study and its companion, the cortical and subcortical connections of the medial belt region of the marmoset monkey auditory cortex were compared with the core region. The main objective was to document anatomical features that account for functional differences observed between areas. Injections of retrograde and bi-directional anatomical tracers targeted two core areas (A1 and R), and two medial belt areas (rostromedial [RM] and caudomedial [CM]). Topographically distinct patterns of connections were revealed among subdivisions of the medial geniculate complex (MGC) and multisensory thalamic nuclei, including the suprageniculate (Sg), limitans (Lim), medial pulvinar (PM), and posterior nucleus (Po). The dominant thalamic projection to the CM was the anterior dorsal division (MGad) of the MGC, whereas the posterior dorsal division (MGpd) targeted RM. CM also had substantial input from multisensory nuclei, especially the magnocellular division (MGm) of the MGC. RM had weak multisensory connections. Corticotectal projections of both RM and CM targeted the dorsomedial quadrant of the inferior colliculus, whereas the CM projection also included a pericentral extension around the ventromedial and lateral portion of the central nucleus. Areas A1 and R were characterized by focal topographic connections within the ventral division (MGv) of the MGC, reflecting the tonotopic organization of both core areas. The results indicate that parallel subcortical pathways target the core and medial belt regions and that RM and CM represent functionally distinct areas within the medial belt auditory cortex.