Dynamics Of Neuronal Responses Research Articles

Perceptual Texture Dimensions Modulate Neuronal Response Dynamics in Visual Cortical Area V4.

Texture is an important visual attribute for surface pattern discrimination and therefore object segmentation, but the neural bases of texture perception are largely unknown. Previously, we demonstrated that the responses of V4 neurons to naturalistic texture patches are sensitive to four key features of human texture perception: coarseness, directionality, regularity, and contrast. To begin to understand how distinct texture perception emerges from the dynamics of neuronal responses, in 2 macaque monkeys (1 male, 1 female), we investigated the relative contribution of the four texture attributes to V4 responses in terms of the strength and timing of response modulation. We found that the different feature dimensions are associated with different temporal dynamics. Specifically, the response modulation associated with directionality and regularity was significantly delayed relative to that associated with coarseness and contrast, suggesting that the latter are fundamentally simpler feature dimensions. The population of texture-selective neurons could be grouped into multiple clusters based on the combination of feature dimensions encoded, and those subpopulations displayed distinct temporal dynamics characterized by the weighted combinations of multiple features. Finally, we applied a population decoding approach to demonstrate that texture category information can be obtained from short temporal windows across time. These results demonstrate that the representation of different perceptually relevant texture features emerge over time in the responses of V4 neurons. The observed temporal organization provides a framework to interpret how the processing of surface features unfolds in early and midlevel cortical stages, and could ultimately inform the interpretation of perceptual texture dynamics.SIGNIFICANCE STATEMENT To delineate how neuronal responses underlie our ability to perceive visual textures, we related four key perceptual dimensions (coarseness, directionality, regularity, and contrast) of naturalistic textures to the strength and timing of modulation of neuronal responses in area V4, an intermediate stage in the form-processing, ventral visual pathway. Our results provide the first characterization of V4 temporal dynamics for texture encoding along perceptually defined axes.

Spatiotemporal Dynamics of Single and Paired Pulse TMS-EEG Responses

For physiological brain function a particular balance between excitation and inhibition is essential. Paired pulse transcranial magnetic stimulation (TMS) can estimate cortical excitability and the relative contribution of inhibitory and excitatory networks. Combining TMS with electroencephalography (EEG) enables additional assessment of the spatiotemporal dynamics of neuronal responses in the stimulated brain. This study aims to evaluate the spatiotemporal dynamics and stability of single and paired pulse TMS-EEG responses, and assess long intracortical inhibition (LICI) at the cortical level. Twenty-five healthy subjects were studied twice, approximately one week apart. Manual coil positioning was applied in sixteen subjects and robot-guided positioning in nine. Both motor cortices were stimulated with 50 single pulses and 50 paired pulses at each of the five interstimulus intervals (ISIs): 100, 150, 200, 250 and 300 ms. To assess stability and LICI, the intraclass correlation coefficient and cluster-based permutation analysis were used. We found great resemblance in the topographical distribution of the characteristic TMS-EEG components for single and paired pulse TMS. Stimulation of the dominant and non-dominant hemisphere resulted in a mirrored spatiotemporal dynamics. No significant effect on the TMS-EEG responses was found for either stimulated hemisphere, time or coil positioning method, indicating the stability of both single and paired pulse TMS-EEG responses. For all ISIs, LICI was characterized by significant suppression of the late N100 and P180 components in the central areas, without affecting the early P30, N45 and P60 components. These observations in healthy subjects can serve as reference values for future neuropsychiatric and pharmacological studies.

Diverse Neuron Properties and Complex Network Dynamics in the Cerebellar Cortical Inhibitory Circuit.

Neuronal inhibition can be defined as a spatiotemporal restriction or suppression of local microcircuit activity. The importance of inhibition relies in its fundamental role in shaping signal processing in single neurons and neuronal circuits. In this context, the activity of inhibitory interneurons proved the key to endow networks with complex computational and dynamic properties. In the last 50 years, the prevailing view on the functional role of cerebellar cortical inhibitory circuits was that excitatory and inhibitory inputs sum spatially and temporally in order to determine the motor output through Purkinje cells (PCs). Consequently, cerebellar inhibition has traditionally been conceived in terms of restricting or blocking excitation. This assumption has been challenged, in particular in the cerebellar cortex where all neurons except granule cells (and unipolar brush cells in specific lobules) are inhibitory and fire spontaneously at high rates. Recently, a combination of electrophysiological recordings in vitro and in vivo, imaging, optogenetics and computational modeling, has revealed that inhibitory interneurons play a much more complex role in regulating cerebellar microcircuit functions: inhibition shapes neuronal response dynamics in the whole circuit and eventually regulate the PC output. This review elaborates current knowledge on cerebellar inhibitory interneurons [Golgi cells, Lugaro cells (LCs), basket cells (BCs) and stellate cells (SCs)], starting from their ontogenesis and moving up to their morphological, physiological and plastic properties, and integrates this knowledge with that on the more renown granule cells and PCs. We will focus on the circuit loops in which these interneurons are involved and on the way they generate feed-forward, feedback and lateral inhibition along with complex spatio-temporal response dynamics. In this perspective, inhibitory interneurons emerge as the real controllers of cerebellar functioning.

Patterns of interaction of coupled reaction–diffusion systems of the FitzHugh–Nagumo type

Motivated by the dynamics of neuronal responses, we analyze the dynamics of the FitzHugh–Nagumo slow–fast system with diffusion and coupling. In the case of diffusion, the system provides a canonical example of Turing–Hopf bifurcation. By analyzing the linear stability of the local equilibrium, the occurrence of Turing–Hopf bifurcation, Turing–Turing bifurcation and coupled Turing–Hopf bifurcation are obtained. The normal form associated with the Turing–Hopf bifurcation is obtained by using the procedure of Song for calculating the normal form of PDEs. Further, in the case of two coupled FitzHugh–Nagumo reaction–diffusion, the Turing–Hopf–Turing bifurcation occurs, and we also find the case about the spatial resonance of Turing–Turing bifurcation arising, and two kinds spatially steady-state solutions are found which are synchronous or anti-phased. Finally, sample numerical results are reported.

Neuronal Responses of Antennal Olfactory Sensilla to Insect Chemical Repellents in the Yellow Fever Mosquito, Aedes aegypti.

The yellow fever mosquito, Aedes aegypti, is a vector of many human diseases such as yellow fever, dengue fever, and Zika. As insecticide resistance has been widely reported, chemical repellents have been adopted as alternative options for mosquito and mosquito-borne disease control. This study characterized the responses of olfactory receptor neurons (ORNs) in different types of antennal olfactory sensilla in Ae. aegypti to 48 chemicals that exhibited repellent activity in various insect species. Both excitatory and inhibitory responses were observed from ORNs in response to these chemicals and differential tuning properties were also observed among ORNs. Remarkable excitatory responses were recorded from the ORNs in sensilla SST1, SST2, SBTI, SBTII, and LST2, while inhibitory activities were detected from a neuron in sensillum SST2 in response to several terpene/terpenoid compounds. Moreover, the temporal dynamics of neuronal responses were found to be compound-specific and concentration-dependent. Hierarchical cluster analysis and principal component analysis of the response to each compound across ORNs in seven types of olfactory sensilla in Ae. aegypti revealed that odor reception depended not only on chemical class but also specific chemical structure. Results of this study give new insights into the sensory physiology of Aedes mosquitoes to the chemical repellents and should contribute to the development of new repellent reagents for human protection.

Platform Session – NIBS: Spatiotemporal dynamics of single and paired pulse TMS-EEG responses in healthy subjects

Introduction Transcranial magnetic stimulation (TMS) is used for assessing cortical excitability in a variety of neurological disorders. Additional information from inhibitory and excitatory networks can be obtained with paired pulse stimulation. Combining TMS with electroencephalography (EEG) allows assessment of the spatiotemporal dynamics of neuronal responses in the stimulated brain. This study aims to evaluate the spread and distribution of single and paired pulse TMS-EEG responses in healthy controls. As cortical excitability is modified in various central nervous system disorders and for central acting drugs, these patterns can serve as a reference for future neurological and pharmacological studies. Methods Thirty healthy subjects (10 males, mean age 28.4 ± 8.2 years) underwent a single and paired pulse TMS-EEG session. Both motor cortices were stimulated with 50 single pulses and 50 paired pulses (intensity 120% of resting motor threshold) at interstimulus intervals (ISIs): 50, 100, 150, 200, 250 and 300 ms. The cluster based permutation test (FieldTrip; http://www.fieldtriptoolbox.org ) was used to analyze the spatiotemporal dynamics of the TMS-EEG response. Significant clusters were formed based on adjacent time bins and neighboring electrodes using 64-channel EEG data. Results Single pulse TMS-EEG responses showed the characteristic P30, N45, P55, N100 and P180 components at channel Cz. The P30 cluster was located centro-parietal in the ipsilateral hemisphere, the N45 centro-frontal contralateral, the P55 parieto-temporal ipsilateral, the N100 central contralateral and the P180 central contralateral and parieto-temporal ipsilateral. Both hemispheres showed a mirrored single pulse TMS-EEG response. For ISI 250 ms, the paired pulse TMS-EEG response also showed the characteristic components at Cz. However, the amplitudes were much smaller compared to single pulse stimulation. Furthermore, fewer, smaller and shorter-lasting significant clusters were found. For ISI 100 ms, no TMS-EEG components were visible at Cz and the response amplitude was much smaller compared to the single pulse response. Next, we will also compare single and paired pulse responses for the other ISIs (50, 150, 200 and 300 ms). Conclusion Stimulation of both hemispheres showed a mirrored single pulse TMS-EEG response. Paired pulse stimulation resulted in fewer, smaller and shorter-lasting clusters compared to single pulse TMS. In combination with a smaller response amplitude, this indicates inhibition of cortical excitability after a conditioning first stimulus. These spatiotemporal dynamics of the single and paired pulse TMS-EEG responses in healthy controls can serve as reference values for future TMS-EEG studies.

Dynamic population codes of multiplexed stimulus features in primate area MT.

The middle-temporal area (MT) of primate visual cortex is critical in the analysis of visual motion. Single-unit studies suggest that the response dynamics of neurons within area MT depend on stimulus features, but how these dynamics emerge at the population level, and how feature representations interact, is not clear. Here, we used multivariate classification analysis to study how stimulus features are represented in the spiking activity of populations of neurons in area MT of marmoset monkey. Using representational similarity analysis we distinguished the emerging representations of moving grating and dot field stimuli. We show that representations of stimulus orientation, spatial frequency, and speed are evident near the onset of the population response, while the representation of stimulus direction is slower to emerge and sustained throughout the stimulus-evoked response. We further found a spatiotemporal asymmetry in the emergence of direction representations. Representations for high spatial frequencies and low temporal frequencies are initially orientation dependent, while those for high temporal frequencies and low spatial frequencies are more sensitive to motion direction. Our analyses reveal a complex interplay of feature representations in area MT population response that may explain the stimulus-dependent dynamics of motion vision.NEW & NOTEWORTHY Simultaneous multielectrode recordings can measure population-level codes that previously were only inferred from single-electrode recordings. However, many multielectrode recordings are analyzed using univariate single-electrode analysis approaches, which fail to fully utilize the population-level information. Here, we overcome these limitations by applying multivariate pattern classification analysis and representational similarity analysis to large-scale recordings from middle-temporal area (MT) in marmoset monkeys. Our analyses reveal a dynamic interplay of feature representations in area MT population response.

Key factors dominating the neural coding preference to 1/f signal

Experiments have demonstrated that cortical and sensory neurons prefer to response to signals with characteristics of long-term correlation or 1/f noise feature better than signals with no correlation like white-noise-type [1]. In order to study the underlying mechanism, we built up a cortical neuronal model [2] based on Hodgkin-Huxley theory to study the correlations between neuron kinetics and signal statistics. Interestingly, we observed that (see Figure 1a,b) white-noise-type signal (cutoff frequency >10000Hz) is hard to induce action potentials unless signals with very strong intensity while 1/f signal and low-pass filtered white noise type signal (cutoff frequency <1000Hz) can easily induce action potentials with high firing rate at low signal intensity (quantified by signal standard deviation STD), see Figure ​Figure1a.1a. Moreover, the half-height duration of action potentials is also varying with more sensitivity to 1/f signal or filtered white noise than pure white noise (Figure ​(Figure1b).1b). In addition, neural firing rate and spike duration are more sensitive to 1/f signal than filtered white noise. This is a clear positive evidence of neuronal coding preference to signals with long-term correlations. Figure 1 Interactions among neuron kinetics and signal statistics. a) Firing rate vs signal STD for white noise, filtered white noise and 1/f noise. b) Half-height duration of action potentials vs signal STD for white noise, filtered white noise and 1/f noise. ... To further reveal the key factors dominating the preference of neuronal dynamics to colored and white noise, we systematically varied the values of Na+ and K+ channel time constants and channel rate constants. Figure ​Figure1c1c showed that the firing rate doesn't change much as a function of sodium activation time constant (τm) for a given 1/f signal (STD = 1). However, the firing rate decrease dramatically with an increase of sodium inactivation time constant (τh) or potassium activation time constant (τn) for this signal. For very large τh and τn, neuronal response dynamics start to be saturate for all signals, see Figure ​Figure1d.1d. These results indicate that both sodium inactivation time constant (τh) and potassium activation time constant (τn) may be the key factors dominating neural coding preference to signals with different correlated statistic features. In sum, this study demonstrated that ionic channel time constant of sodium inactivation and potassium activation may be the dominating factors accounting for the neuronal spiking sensitivity favorable to signals with temporal correlations.

Basal forebrain dynamics during nonassociative and associative olfactory learning.

Cholinergic and GABAergic projections from the horizontal diagonal band (HDB) and medial preoptic area (MCPO) of the basal forebrain to the olfactory system are associated with odor discrimination and odor learning, as well as modulation of neural responses in olfactory structures. Whereas pharmacological and lesion studies give insights into the functional role of these modulatory inputs on a slow timescale, the response dynamics of neurons in the HDB/MCPO during olfactory behaviors have not been investigated. In this study we examined how these neurons respond during two olfactory behaviors: spontaneous investigation of odorants and odor-reward association learning. We observe rich heterogeneity in the response dynamics of individual HDB/MCPO neurons, with a substantial fraction of neurons exhibiting task-related modulation. HDB/MCPO neurons show both rapid and transient responses during bouts of odor investigation and slow, long-lasting modulation of overall response rate based on behavioral demands. Specifically, baseline rates were higher during the acquisition phase of an odor-reward association than during spontaneous investigation or the recall phase of an odor reward association. Our results suggest that modulatory projections from the HDB/MCPO are poised to influence olfactory processing on multiple timescales, from hundreds of milliseconds to minutes, and are therefore capable of rapidly setting olfactory network dynamics during odor processing and learning.

Liouville Correspondence Between the Modified KdV Hierarchy and Its Dual Integrable Hierarchy

Motivated by the dynamics of neuronal responses, we analyze the dynamics of the Fitzhugh-Nagumo slow-fast system with delayed self-coupling. This system provides a canonical example of a canard explosion for sufficiently small delays. Beyond this regime, delays significantly enrich the dynamics, leading to mixed-mode oscillations, bursting and chaos. These behaviors emerge from a delay-induced subcritical Bogdanov-Takens instability arising at the fold points of the S-shaped critical manifold. Underlying the transition from canard-induced to delay-induced dynamics is an abrupt switch in the nature of the Hopf bifurcation.

Complex Oscillations in the Delayed FitzHugh–Nagumo Equation

Motivated by the dynamics of neuronal responses, we analyze the dynamics of the FitzHugh–Nagumo slow–fast system with delayed self-coupling. This system provides a canonical example of a canard explosion for sufficiently small delays. Beyond this regime, delays significantly enrich the dynamics, leading to mixed-mode oscillations, bursting and chaos. These behaviors emerge from a delay-induced subcritical Bogdanov–Takens instability arising at the fold points of the S-shaped critical manifold. Underlying the transition from canard-induced to delay-induced dynamics is an abrupt switch in the nature of the Hopf bifurcation.

Activation of InsP₃ receptors is sufficient for inducing graded intrinsic plasticity in rat hippocampal pyramidal neurons.

The synaptic plasticity literature has focused on establishing necessity and sufficiency as two essential and distinct features in causally relating a signaling molecule to plasticity induction, an approach that has been surprisingly lacking in the intrinsic plasticity literature. In this study, we complemented the recently established necessity of inositol trisphosphate (InsP3) receptors (InsP3R) in a form of intrinsic plasticity by asking if InsP3R activation was sufficient to induce intrinsic plasticity in hippocampal neurons. Specifically, incorporation of d-myo-InsP3 in the recording pipette reduced input resistance, maximal impedance amplitude, and temporal summation but increased resonance frequency, resonance strength, sag ratio, and impedance phase lead. Strikingly, the magnitude of plasticity in all these measurements was dependent on InsP3 concentration, emphasizing the graded dependence of such plasticity on InsP3R activation. Mechanistically, we found that this InsP3-induced plasticity depended on hyperpolarization-activated cyclic nucleotide-gated channels. Moreover, this calcium-dependent form of plasticity was critically reliant on the release of calcium through InsP3Rs, the influx of calcium through N-methyl-d-aspartate receptors and voltage-gated calcium channels, and on the protein kinase A pathway. Our results delineate a causal role for InsP3Rs in graded adaptation of neuronal response dynamics, revealing novel regulatory roles for the endoplasmic reticulum in neural coding and homeostasis.

Image familiarization sharpens response dynamics of neurons in inferotemporal cortex.

Repeated viewing of an image over days and weeks induces a marked reduction in the strength with which neurons in monkey inferotemporal cortex respond to it. The processing advantage that attaches to this reduction is unknown. One possibility is that truncation of the response to a familiar image leaves neurons in a state of readiness to respond to ensuing images and thereby enhances their ability to track rapidly changing displays. We explored this possibility by assessing neuronal responses to familiar and novel images in rapid serial visual displays. Inferotemporal neurons responded more strongly to familiar than to novel images in such displays. The effect was stronger among putative inhibitory neurons than among putative excitatory neurons. A comparable effect occurred at the level of the scalp potential in humans. We conclude that long-term familiarization sharpens the response dynamics of neurons in both monkey and human extrastriate visual cortex.

Specific Modulation by Sound of Primary Visual Cortex Neuron Responses to Light Stimuli of Different Intensities in Rabbits

Experiments were performed on four European rabbits (Orictolagus cuniculus) and included extracellular recordings of a total of 92 neurons. The first series of experiments recorded the responses of 63 neurons to substitution of visual stimuli presented in pairs (pairs with intensities of 0.28 and 1; 1 and 3; 3 and 6; 6 and 8.5; 8.5 and 14; 14 and 17; and 17 and 20 cd/m2). The same stimulus substitutions were then presented with sound (70 dB, 2000 Hz, 40 msec). Neurons did not respond directly to the sound. Two groups of neurons were found. Responses to “light + sound” complexes (in the interval 40–100 msec from the moment of stimulus substitution) increased by a mean 41% (p < 0.0001) at the lowest stimulus intensities in neurons of group 1 (31%). As light intensity increased, discharges in response to the complex decreased to or even below the level of responses to light. Neurons of group 2 (19%) showed the opposite properties: at low light intensities, responses to complexes were comparable with or even smaller than responses to light, while at high intensities (14–20 cd/m2) responses were significantly different (p < 0.05) from responses to light (by 20–39%). The next series of experiments reconstructed the sensory vector spaces on the basis of the responses to 29 neurons to light stimuli of eight different intensities and “sound + light” complexes. Sound was also found to have a double action on the sensory spaces of complexes. Some neurons showed marked increases in the angular distance between the two lowest-intensity stimuli (0.28 and 1 cd/m2), while others showed an increase in the angular distance for the highest intensities. These changes in the structure of the spaces were consisted with the neuron groups identified in the first two series. Comparison of the dynamics of neuron responses and the amplitudes of evoked potentials in the same stimulation conditions showed that there was significant similarity. Thus, these data lead to the conclusion that modulation of visual cortex neuron activity by sound occurs in a complex, nonlinear manner.

Temporal Dynamics of 2D Motion Integration for Ocular Following in Macaque Monkeys

Several recent studies have shown that extracting pattern motion direction is a dynamical process where edge motion is first extracted and pattern-related information is encoded with a small time lag by MT neurons. A similar dynamics was found for human reflexive or voluntary tracking. Here, we bring an essential, but still missing, piece of information by documenting macaque ocular following responses to gratings, unikinetic plaids, and barber-poles. We found that ocular tracking was always initiated first in the grating motion direction with ultra-short latencies (approximately 55 ms). A second component was driven only 10-15 ms later, rotating tracking toward pattern motion direction. At the end the open-loop period, tracking direction was aligned with pattern motion direction (plaids) or the average of the line-ending motion directions (barber-poles). We characterized the dependency on contrast of each component. Both timing and direction of ocular following were quantitatively very consistent with the dynamics of neuronal responses reported by others. Overall, we found a remarkable consistency between neuronal dynamics and monkey behavior, advocating for a direct link between the neuronal solution of the aperture problem and primate perception and action.

Subpopulations of neurons in visual area V2 perform differentiation and integration operations in space and time

The interconnected areas of the visual system work together to find object boundaries in visual scenes. Primary visual cortex (V1) mainly extracts oriented luminance boundaries, while secondary visual cortex (V2) also detects boundaries defined by differences in texture. How the outputs of V1 neurons are combined to allow for the extraction of these more complex boundaries in V2 is as of yet unclear. To address this question, we probed the processing of orientation signals in single neurons in V1 and V2, focusing on response dynamics of neurons to patches of oriented gratings and to combinations of gratings in neighboring patches and sequential time frames. We found two kinds of response dynamics in V2, both of which were different from those of V1 neurons. While V1 neurons in general preferred one orientation, one subpopulation of V2 neurons (“transient”) showed a temporally dynamic preference, resulting in a preference for changes in orientation. The second subpopulation of V2 neurons (“sustained”) responded similarly to V1 neurons, but with a delay. The dynamics of nonlinear responses to combinations of gratings reinforced these distinctions: the dynamics enhanced the preference of V1 neurons for continuous orientations and the preference of V2 transient neurons for discontinuous ones. We propose that transient neurons in V2 perform a differentiation operation on the V1 input, both spatially and temporally, while the sustained neurons perform an integration operation. We show that a simple feedforward network with delayed inhibition can account for the temporal but not for the spatial differentiation operation.

Context-Dependent Changes in Functional Circuitry in Visual Area MT

Animals can flexibly change their behavior in response to a particular sensory stimulus; the mapping between sensory and motor representations in the brain must therefore be flexible as well. Changes in the correlated firing of pairs of neurons may provide a metric of changes in functional circuitry during behavior. We studied dynamic changes in functional circuitry by analyzing the noise correlations of simultaneously recorded MT neurons in two behavioral contexts: one that promotes cooperative interactions between the two neurons and another that promotes competitive interactions. We found that identical visual stimuli give rise to differences in noise correlation in the two contexts, suggesting that MT neurons receive inputs of central origin whose strength changes with the task structure. The data are consistent with a mixed feature-based attentional strategy model in which the animal sometimes alternates attention between opposite directions of motion and sometimes attends to the two directions simultaneously.

The h Channel Mediates Location Dependence and Plasticity of Intrinsic Phase Response in Rat Hippocampal Neurons

The presence of phenomenological inductances in neuronal membrane has been known for more than one-half a century. Despite this, the dramatic contributions of such inductive elements to the amplitude and, especially, phase of neuronal impedance, and their roles in modulating temporal dynamics of neuronal responses have surprisingly remained unexplored. In this study, we demonstrate that the h channel contributes a location-dependent and plastic phenomenological inductive component to the input impedance of CA1 pyramidal neurons. Specifically, we show that the h channels introduce an apparent negative delay in the local voltage response of these neurons with respect to the injected current within the theta frequency range. The frequency range and the extent of this lead expand with increases in h current either through hyperpolarization, or with increasing distance of dendritic location from the soma. We also demonstrate that a spatially widespread increase in this inductive phase component accompanies long-term potentiation. Finally, using impedance analysis, we show that both location and activity dependence of intrinsic phase response are attributable not to changes in a capacitive or a leak component, but to changes in h-channel properties. Our results suggest that certain voltage-gated ion channels can differentially regulate internal time delays within neurons, thus providing them with an independent control mechanism in temporal coding of neuronal information. Our analyses and results also establish impedance as a powerful measure of intrinsic dynamics and excitability, given that it quantifies temporal relationships among signals and excitability as functions of input frequency.

Activity of Vestibular Nuclei Neurons During Vestibular and Optokinetic Stimulation in the Alert Mouse

As a result of the availability of genetic mutant strains and development of noninvasive eye movements recording techniques, the mouse stands as a very interesting model for bridging the gap among behavioral responses, neuronal response dynamics studied in vivo, and cellular mechanisms investigated in vitro. Here we characterized the responses of individual neurons in the mouse vestibular nuclei during vestibular (horizontal whole body rotations) and full field visual stimulation. The majority of neurons ( approximately 2/3) were sensitive to vestibular stimulation but not to eye movements. During the vestibular-ocular reflex (VOR), these neurons discharged in a manner comparable to the "vestibular only" (VO) neurons that have been previously described in primates. The remaining neurons [eye-movement-sensitive (ES) neurons] encoded both head-velocity and eye-position information during the VOR. When vestibular and visual stimulation were applied so that there was sensory conflict, the behavioral gain of the VOR was reduced. In turn, the modulation of sensitivity of VO neurons remained unaffected, whereas that of ES neurons was reduced. ES neurons were also modulated in response to full field visual stimulation that evoked the optokinetic reflex (OKR). Mouse VO neurons, however, unlike their primate counterpart, were not modulated during OKR. Taken together, our results show that the integration of visual and vestibular information in the mouse vestibular nucleus is limited to a subpopulation of neurons which likely supports gaze stabilization for both VOR and OKR.

A Dynamic Nonlinearity and Spatial Phase Specificity in Macaque V1 Neurons

While studying the visual response dynamics of neurons in the macaque primary visual cortex (V1), we found a nonlinearity of temporal response that influences the visual functions of V1 neurons. Simple cells were recorded in all layers of V1; the nonlinearity was strongest in neurons located in layer 2/3. We recorded the spike responses to optimal sinusoidal gratings that were displayed for 100 ms, a temporal step response. The step responses were measured at many spatial phases of the grating stimulus. To judge whether simple cell behavior was consistent with linear temporal integration, the decay of the 100 ms step response at the preferred spatial phase was used to predict the step response at the opposite spatial phase. Responses in layers 4B and 4C were mostly consistent with a linear-plus-static-nonlinearity cascade model. However, this was not true in layer 2/3 where most cells had little or no step responses at the opposite spatial phase. Many layer 2/3 cells had transient preferred-phase responses but did not respond at the offset of the opposite-phase stimuli, indicating a dynamic nonlinearity. A different stimulus sequence, rapidly presented random sinusoids, also produced the same effect, with layer 2/3 simple cells exhibiting elevated spike rates in response to stimuli at one spatial phase but not 180 degrees away. The presence of a dynamic nonlinearity in the responses of V1 simple cells indicates that first-order analyses often capture only a fraction of neuronal behavior. The visual implication of our results is that simple cells in layer 2/3 are spatial phase-sensitive detectors that respond to contrast boundaries of one sign but not the opposite.