Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex

Gain modulation from background synaptic input

Gain modulation is a prominent feature of neuronal activity recorded in behaving animals, but the mechanism by which it occurs is unknown. By introducing a barrage of excitatory and inhibitory synaptic conductances that mimics conditions encountered in vivo into pyramidal neurons in slices of rat somatosensory cortex, we show that the gain of a neuronal response to excitatory drive can be modulated by varying the level of "background" synaptic input. Simultaneously increasing both excitatory and inhibitory background firing rates in a balanced manner results in a divisive gain modulation of the neuronal response without appreciable signal-independent increases in firing rate or spike-train variability. These results suggest that, within active cortical circuits, the overall level of synaptic input to a neuron acts as a gain control signal that modulates responsiveness to excitatory drive.

Visual cortex neurons of monkeys and cats: temporal dynamics of the contrast response function

Cortical neurons display two fundamental nonlinear response characteristics: contrast-set gain control (also termed contrast normalization) and response expansion (also termed half-squaring). These nonlinearities could play an important role in forming and maintaining stimulus selectivity during natural viewing, but only if they operate well within the time frame of a single fixation. To analyze the temporal dynamics of these nonlinearities, we measured the responses of individual neurons, recorded from the primary visual cortex of monkeys and cats, as a function of the contrast of transient stationary gratings that were presented for a brief interval (200 ms). We then examined 1) the temporal response profile (i.e., the post stimulus time histogram) as a function of contrast and 2) the contrast response function throughout the course of the temporal response. We found that the shape and complexity of the temporal response profile varies considerably from cell to cell. However, within a given cell, the shape remains relatively invariant as a function of contrast and appears to be simply scaled and shifted. Stated quantitatively, approximately 95% of the variation in the temporal responses as a function of contrast could be accounted for by scaling and shifting the average poststimulus time histogram. Equivalently, we found that the overall shape of the contrast response function (measured every 2 ms) remains relatively invariant from the onset through the entire temporal response. Further, the contrast-set gain control and the response expansion are fully expressed within the first 10 ms after the onset of the response. Stated quantitatively, the same, scaled Naka-Rushton equation (with the same half-saturation contrast and expansive response exponent) provides a good fit to the contrast response function from the first 10 ms through the last 10 ms of the temporal response. Based upon these measurements, it appears as though the two nonlinear properties, contrast-set gain control and response expansion, are present in full strength, virtually instantaneously, at the onset of the response. This observation suggests that response expansion and contrast-set gain control can influence the performance of visual cortex neurons very early in a single fixation, based on the contrast within that fixation. In the DISCUSSION, we consider the implications of the results within the context of 1) slower types of contrast gain control, 2) discrimination performance, 3) drifting steady-state measurements, 4) functional models that incorporate response expansion and contrast normalization, and 5) structural models of the biochemical and biophysical neural mechanisms.

How noise contributes to contrast invariance of orientation tuning in cat visual cortex

The width of the orientation tuning curves of the spike response of neurons in V1 is invariant to contrast. This property constrains the possible mechanisms underlying orientation selectivity. It has been suggested that noise circumvents the iceberg effect that would prevent contrast invariance in the purely feedforward mechanism. Here we investigate systematically how noise contributes to the contrast invariance of orientation tuning curves in V1. We study three models of increasing complexity: a simple threshold-linear firing rate model, a leaky integrate-and-fire model, and a conductance-based model. We show that the noise transmutes the threshold nonlinearity of the input-output relationships into an approximate power law without a threshold within some firing rate range. This implies that, under certain conditions which are derived here, the tuning of the neuron output is approximately contrast invariant. In particular we show that this mechanism for contrast invariance requires that the neuron firing rate must not be too large and that increasing or lowering the contrast too much destroys this invariance. We also show that if this mechanism operates in V1, the spike response, R, and average voltage response V of the neurons in V1 should vary with the contrast, C, according to R(C)gamma proportional to V(C)gamma. The exponent gamma can be estimated from the amount by which the spike tuning curve is sharpened with respect to the voltage tuning curves of the neurons. This prediction does not depend on the specifics of the model and can be tested experimentally.

Constraints on the source of short-term motion adaptation in macaque area MT. II. tuning of neural circuit mechanisms

Neurons in area MT, a motion-sensitive area of extrastriate cortex, respond to a step of target velocity with a transient-sustained firing pattern. The transition from a high initial firing rate to a lower sustained rate occurs over a time course of 20-80 ms and is considered a form of short-term adaptation. In the present paper, we compared the tuning of the adaptation to the neuron's tuning to direction and speed. The tuning of adaptation was measured with a condition/test paradigm in which a testing motion of the preferred direction and speed of the neuron under study was preceded by a conditioning motion: the direction and speed of the conditioning motion were varied systematically. The response to the test motion depended strongly on the direction of the conditioning motion. It was suppressed in almost all neurons by conditioning motion in the same direction and could be either suppressed or enhanced by conditioning motion in the opposite direction. Even in neurons that showed suppression for target motion in the nonpreferred direction, the adaptation and response direction tuning were the same. The speed tuning of adaptation was linked much less tightly to the speed tuning of the response of the neuron under study. For just more than 50% of neurons, the preferred speed of adaptation was more than 1 log unit different from the preferred response speed. Many neurons responded best when slow motions were followed by faster motions (acceleration) or vice versa (deceleration), suggesting that MT neurons may encode information about the change of target velocity over time. Finally, adaptation by conditioning motions of different directions, but not different speeds, altered the latency of the response to the test motion. The adaptation of latency recovered with shorter intervals between the conditioning and test motions than did the adaptation of response size, suggesting that latency and amplitude adaptation are mediated by separate mechanisms. Taken together with the companion paper, our data suggest that short-term motion adaptation in MT is a consequence of the neural circuit in MT and is not mediated by either input-specific mechanisms or intrinsic mechanisms related to the spiking of individual neurons. The circuit responsible for adaptation is tuned for both speed and direction and has the same direction tuning as the circuit responsible for the initial response of MT neurons.

The spatial properties of opponent-motion normalization

The final stage of the Adelson-Bergen model [J. Opt. Soc. Am. A 2 (1985) 284] computes net motion as the difference between directionally opposite energies E(L) and E(R). However, Georgeson and Scott-Samuel [Vis. Res. 39 (1999) 4393] found that human direction discrimination is better described by motion contrast (C(m))--a metric where opponent energy (E(L)-E(R)) is divided by flicker energy (E(L)+E(R)). In the present paper, we used a lateral masking paradigm to investigate the spatial properties of flicker energy involved in the normalization of opponent energy. Observers discriminated between left and right motion while viewing a checkerboard in which half of the checks contained a drifting sinusoid and the other half contained flicker (i.e. a counterphasing sinusoid). The relative luminance contrasts of flicker and motion checks determined the checkerboard's overall motion contrast C(m). We obtained selectivity functions for opponent-motion normalization by measuring C(m) thresholds whilst varying the orientation, spatial frequency, or size of flicker checks. In all conditions, performance (percent correct) decayed lawfully as we decreased motion contrast, validating the C(m) metric for our stimuli. Thresholds decreased with check size and also improved as we increased either the orientation or spatial-frequency difference between motion and flicker checks. Our data are inconsistent with Heeger-type normalization models [Vis. Neurosci. 9 (1992) 181] in which excitatory inputs are normalized by a non-selective pooling of inhibitory inputs, but data are consistent with the implicit assumption in Georgeson and Scott-Samuel's model that flicker normalization is localized in orientation, scale, and space. However, our lateral masking paradigm leaves open the possibility that the spatial properties of flicker normalization would be different if opponent and flicker energies spatially overlapped. Further characterization of motion contrast will require models of the spatial, temporal, and joint space-time properties of mechanisms mediating opponent-motion and flicker normalization.

LGN input to simple cells and contrast-invariant orientation tuning: an analysis

We develop a new analysis of the lateral geniculate nucleus (LGN) input to a cortical simple cell, demonstrating that this input is the sum of two terms, a linear term and a nonlinear term. In response to a drifting grating, the linear term represents the temporal modulation of input, and the nonlinear term represents the mean input. The nonlinear term, which grows with stimulus contrast, has been neglected in many previous models of simple cell response. We then analyze two scenarios by which contrast-invariance of orientation tuning may arise. In the first scenario, at larger contrasts, the nonlinear part of the LGN input, in combination with strong push-pull inhibition, counteracts the nonlinear effects of cortical spike threshold, giving the result that orientation tuning scales with contrast. In the second scenario, at low contrasts, the nonlinear component of LGN input is negligible, and noise smooths the nonlinearity of spike threshold so that the input-output function approximates a power-law function. These scenarios can be combined to yield contrast-invariant tuning over the full range of stimulus contrast. The model clarifies the contribution of LGN nonlinearities to the orientation tuning of simple cells and demonstrates how these nonlinearities may impact different models of contrast-invariant tuning.

Short-term depression at thalamocortical synapses contributes to rapid adaptation of cortical sensory responses in vivo

In vivo whole-cell recordings revealed that during repeated stimulation, synaptic responses to deflection of facial whiskers rapidly adapt. Extracellular recordings in the somatosensory thalamus revealed that part of the adaptation occurs subcortically, but because cortical adaptation is stronger and recovers more slowly, cortical mechanisms must also contribute. Trains of sensory stimuli that produce profound sensory adaptation did not alter intrinsic membrane properties, including resting membrane potential, input resistance, and current-evoked firing. Synaptic input evoked via intracortical stimulation was also unchanged; however, synaptic input from the somatosensory thalamus was depressed by sensory stimulation, and this depression recovered with a time course matching that of the recovery of sensory responsiveness. These data strongly suggest that synaptic depression of thalamic input to the cortex contributes to the dynamic regulation of neuronal sensitivity during rapid changes in sensory input.

Laminar processing of stimulus orientation in cat visual cortex

One of the most salient features to emerge in visual cortex is sensitivity to stimulus orientation. Here we asked if orientation selectivity, once established, is altered by successive stages of cortical processing. We measured patterns of orientation selectivity at all depths of the cat's visual cortex by making whole-cell recordings with dye-filled electrodes. Our results show that the synaptic representation of orientation indeed changes with position in the microcircuit, as information passes from layer 4 to layer 2+3 to layer 5. At the earliest cortical stage, for simple cells in layer 4, orientation tuning curves for excitation (depolarization) and inhibition (hyperpolarization) had similar peaks (within 0-7 deg, n = 11) and bandwidths. Further, the sharpness of orientation selectivity covaried with receptive field geometry (r = 0.74) - the more elongated the strongest subregion, the shaper the tuning. Tuning curves for complex cells in layer 2+3 also had similar peaks (within 0-4 deg, n = 7) and bandwidths. By contrast, at a later station, layer 5, the preferred orientation for excitation and inhibition diverged such that the peaks of the tuning curves could be as far as 90 deg apart (average separation, 54 deg; n = 6). Our results support the growing consensus that orientation selectivity is generated at the earliest cortical level and structured similarly for excitation and inhibition. Moreover, our novel finding that the relative tuning of excitation and inhibition changes with laminar position helps resolve prior controversy about orientation selectivity at later phases of processing and gives a mechanistic view of how the cortical circuitry recodes orientation.

Dynamics of spatial frequency tuning in macaque V1

Spatial frequency tuning in the lateral geniculate nucleus of the thalamus (LGN) and primary visual cortex (V1) differ substantially. LGN responses are largely low-pass in spatial frequency, whereas the majority of V1 neurons have bandpass characteristics. To study this transformation in spatial selectivity, we measured the dynamics of spatial frequency tuning using a reverse correlation technique. We find that a large proportion of V1 cells show inseparable responses in spatial frequency and time. In several cases, tuning becomes more selective over the course of the response, and the preferred spatial frequency shifts from low to higher frequencies. Many responses also show suppression at low spatial frequencies, which correlates with the increases in response selectivity and the shifts of preferred spatial frequency. These results indicate that suppression plays an important role in the generation of bandpass selectivity in V1.

Coarse-grained reduction and analysis of a network model of cortical response: I. Drifting grating stimuli

We present a reduction of a large-scale network model of visual cortex developed by McLaughlin, Shapley, Shelley, and Wielaard. The reduction is from many integrate-and-fire neurons to a spatially coarse-grained system for firing rates of neuronal subpopulations. It accounts explicitly for spatially varying architecture, ordered cortical maps (such as orientation preference) that vary regularly across the cortical layer, and disordered cortical maps (such as spatial phase preference or stochastic input conductances) that may vary widely from cortical neuron to cortical neuron. The result of the reduction is a set of nonlinear spatiotemporal integral equations for "phase-averaged" firing rates of neuronal subpopulations across the model cortex, derived asymptotically from the full model without the addition of any extra phenomological constants. This reduced system is used to study the response of the model to drifting grating stimuli-where it is shown to be useful for numerical investigations that reproduce, at far less computational cost, the salient features of the point-neuron network and for analytical investigations that unveil cortical mechanisms behind the responses observed in the simulations of the large-scale computational model. For example, the reduced equations clearly show (1) phase averaging as the source of the time-invariance of cortico-cortical conductances, (2) the mechanisms in the model for higher firing rates and better orientation selectivity of simple cells which are near pinwheel centers, (3) the effects of the length-scales of cortico-cortical coupling, and (4) the role of noise in improving the contrast invariance of orientation selectivity.

Cell type- and subcellular position-dependent summation of unitary postsynaptic potentials in neocortical neurons

Theoretical studies predict that the modes of integration of coincident inputs depend on their location and timing. To test these models experimentally, we simultaneously recorded from three neocortical neurons in vitro and investigated the effect of the subcellular position of two convergent inputs on the response summation in the common postsynaptic cell. When scattered over the somatodendritic surface, combination of two coincident excitatory or inhibitory synaptic potentials summed linearly in layer 2/3 pyramidal cells, as well as in GABAergic interneurons. Slightly sublinear summation with connection specific kinetics was observed when convergent inputs targeted closely placed sites on the postsynaptic cell. The degree of linearity of summation also depended on the type of connection, the relative timing of inputs, and the activation state of I(h). The results suggest that, when few inputs are active, the majority of afferent permutations undergo linear integration, maintaining the importance of individual inputs. However, compartment- and connection-specific nonlinear interactions between synapses located close to each other could increase the computational power of individual neurons in a cell type-specific manner.

Cellular mechanisms of infralimbic and prelimbic prefrontal cortical inhibition and dopaminergic modulation of basolateral amygdala neurons in vivo

The basolateral amygdala (BLA) is believed to be involved in schizophrenia, depression, and other disorders that display affective components. The neuronal activity of the BLA, and BLA-mediated affective behaviors, are driven by sensory stimuli transmitted in part from sensory association cortical regions. These same behaviors may be regulated by prefrontal cortical (PFC) inputs to the BLA. However, it is unclear how two sets of glutamatergic inputs to the BLA can impose opposing actions on BLA-mediated behaviors; specifically, it is unclear how PFC inputs exert inhibitory actions over BLA projection neurons. Dopamine (DA) receptor activation enhances BLA-mediated behaviors. Although we have demonstrated that DA suppresses medial PFC inputs to the BLA and enhances sensory cortical inputs, the precise cellular mechanisms for its actions are unknown. In this study we use in vivo intracellular recordings to determine the means by which glutamatergic inputs from the PFC inhibit BLA projection neurons, contrast that with glutamatergic inputs from the association sensory cortex (Te3) that drive BLA projection neurons, and examine the effects of DA receptor activation on neuronal excitability, spontaneous postsynaptic potentials (PSPs), and PFC-evoked PSPs. We found that PFC stimulation inhibits BLA projection neurons by three mechanisms: chloride-mediated hyperpolarization, a persistent decrease in neuronal input resistance, and shunting of PSPs; all effects are possibly attributable to recruitment of inhibitory interneurons. DA receptor activation enhanced neuronal input resistance by a postsynaptic mechanism (via DA D2 receptors), suppressed spontaneously occurring and PFC-evoked PSPs (via DA D1 receptors), and enhanced Te3-evoked PSPs.

Suppression of neural responses to nonoptimal stimuli correlates with tuning selectivity in macaque V1

Neural responses in primary visual cortex (area V1) are selective for the orientation and spatial frequency of luminance-modulated sinusoidal gratings. Selectivity could arise from enhancement of the cell's response by preferred stimuli, suppression by nonoptimal stimuli, or both. Here, we report that the majority of V1 neurons do not only elevate their activity in response to preferred stimuli, but their firing rates are also suppressed by nonoptimal stimuli. The magnitude of suppression is similar to that of enhancement. There is a tendency for net response suppression to peak at orientations near orthogonal to the optimal for the cell, but cases where suppression peaks at oblique orientations are observed as well. Interestingly, selectivity and suppression correlate in V1: orientation and spatial frequency selectivity are higher for neurons that are suppressed by nonoptimal stimuli than for cells that are not. This finding is consistent with the idea that suppression plays an important role in the generation of sharp cortical selectivity. We show that nonlinear suppression is required to account for the data. However, the precise structure of the neural circuitry generating the suppressive signal remains unresolved. Our results are consistent with both feedback and (nonlinear) feed-forward inhibition.

Dynamics and constancy in cortical spatiotemporal patterns of orientation processing

How does the high selectivity to stimulus orientation emerge in the visual cortex? Thalamic feedforward-dominated models of orientation selectivity predict constant selectivity during the visual response, whereas intracortical recurrent models predict dynamic improvement in selectivity. We imaged the cat visual cortex with voltage-sensitive dyes to measure orientation-tuning dynamics of a large neuronal population. Tuning-curve width did not narrow after response onset, whereas the difference between preferred and orthogonal responses (modulation depth) first increased, then declined. We identified a suppression of the evoked responses, referred to as the evoked deceleration-acceleration (DA) notch, which was larger for the orthogonal response. Furthermore, peak selectivity of the tuning curves was contemporaneous with the evoked DA notch. These findings suggest that in the cat brain, sustained visual cortical processing does not narrow orientation tuning; rather, intracortical interactions may amplify modulation depth and suppress the orthogonal response relatively more than the preferred. Thus, feedforward models and recurrent models of orientation selectivity must be combined.

BDNF/trkB signaling in the developmental sculpting of visual connections

Neurotrophins are a family of secreted molecules that have multiple, profound actions on the structure and function of both developing and mature neurons. Neurotrophins exert their influences by signaling through the trk family of receptor tyrosine kinases and the p75 low affinity neurotrophin receptor. Here we review the contributions of neurotrophins to the development of neural circuitry in the mammalian visual system. We emphasize: (1) the role of neurotrophins as components of the cellular mechanisms by which neuroelectric activity sculpts pattern of brain connectivity; and (2) the results of recent experiments suggesting that the trafficking of neurotrophin proteins may be activity dependent.

Opponent inhibition: a developmental model of layer 4 of the neocortical circuit

We model the development of the functional circuit of layer 4 (the input-recipient layer) of cat primary visual cortex. The observed thalamocortical and intracortical circuitry codevelop under Hebb-like synaptic plasticity. Hebbian development yields opponent inhibition: inhibition evoked by stimuli anticorrelated with those that excite a cell. Strong opponent inhibition enables recognition of stimulus orientation in a manner invariant to stimulus contrast. These principles may apply to cortex more generally: Hebb-like plasticity can guide layer 4 of any piece of cortex to create opposition between anticorrelated stimulus pairs, and this enables recognition of specific stimulus patterns in a manner invariant to stimulus magnitude. Properties that are invariant across a cortical column are predicted to be those shared by opponent stimulus pairs; this contrasts with the common idea that a column represents cells with similar response properties.

Local correlation-based circuitry can account for responses to multi-grating stimuli in a model of cat V1

In cortical simple cells of cat striate cortex, the response to a visual stimulus of the preferred orientation is partially suppressed by simultaneous presentation of a stimulus at the orthogonal orientation, an effect known as "cross-orientation inhibition." It has been argued that this is due to the presence of inhibitory connections between cells tuned for different orientations, but intracellular studies suggest that simple cells receive inhibitory input primarily from cells with similar orientation tuning. Furthermore, response suppression can be elicited by a variety of nonpreferred stimuli at all orientations. Here we study a model circuit that was presented previously to address many aspects of simple cell orientation tuning, which is based on local intracortical connectivity between cells of similar orientation tuning. We show that this model circuit can account for many aspects of cross-orientation inhibition and, more generally, of response suppression by nonpreferred stimuli and of other nonlinear properties of responses to stimulation with multiple gratings.

Contrast-dependent nonlinearities arise locally in a model of contrast-invariant orientation tuning

We study a recently proposed "correlation-based," push-pull model of the circuitry of layer 4 of cat visual cortex. This model was previously shown to explain the contrast-invariance of cortical orientation tuning. Here we show that it can simultaneously account for several contrast-dependent (c-d) "nonlinearities" in cortical responses. These include an advance with increasing contrast in the temporal phase of response to a sinusoidally modulated stimulus; a change in shape of the temporal frequency tuning curve, so that higher temporal frequencies may give little or no response at low contrast but reasonable responses at high contrast; and contrast saturation that occurs at lower contrasts in cortex than in the lateral geniculate nucleus (LGN). In the context of the model circuit, these properties arise from a mixture of nonlinear cellular and synaptic mechanisms: short-term synaptic depression, spike-rate adaptation, contrast-induced changes in cellular conductance, and the nonzero spike threshold. The former three mechanisms are sufficient to explain the experimentally observed increase in c-d phase advance in cortex relative to LGN. The c-d changes in temporal frequency tuning arise as a threshold effect: voltage modulations in response to higher-frequency inputs are only slightly above threshold at lower contrast, but become robustly suprathreshold at higher contrast. The other three nonlinear mechanisms also play a crucial role in this result, allowing contrast dependence of temporal frequency tuning to coexist with contrast-invariance of orientation tuning. Contrast saturation, and the observation that responses to stimuli of increasing temporal frequency saturate at increasingly high contrasts, can be induced both by the model's push-pull inhibition and by synaptic depression. Previous proposals explained these nonlinear response properties by assuming contrast-invariant orientation tuning as a starting point, and adding normalization by shunting inhibition derived equally from cells of all preferred orientations. The present proposal simultaneously explains both contrast-invariant orientation tuning and these contrast-dependent nonlinearities and requires only processing that is local in orientation, in agreement with intracellular measurements.

Natural signal statistics and sensory gain control

We describe a form of nonlinear decomposition that is well-suited for efficient encoding of natural signals. Signals are initially decomposed using a bank of linear filters. Each filter response is then rectified and divided by a weighted sum of rectified responses of neighboring filters. We show that this decomposition, with parameters optimized for the statistics of a generic ensemble of natural images or sounds, provides a good characterization of the nonlinear response properties of typical neurons in primary visual cortex or auditory nerve, respectively. These results suggest that nonlinear response properties of sensory neurons are not an accident of biological implementation, but have an important functional role.

How simple cells are made in a nonlinear network model of the visual cortex

Simple cells in the striate cortex respond to visual stimuli in an approximately linear manner, although the LGN input to the striate cortex, and the cortical network itself, are highly nonlinear. Although simple cells are vital for visual perception, there has been no satisfactory explanation of how they are produced in the cortex. To examine this question, we have developed a large-scale neuronal network model of layer 4Calpha in V1 of the macaque cortex that is based on, and constrained by, realistic cortical anatomy and physiology. This paper has two aims: (1) to show that neurons in the model respond like simple cells. (2) To identify how the model generates this linearized response in a nonlinear network. Each neuron in the model receives nonlinear excitation from the lateral geniculate nucleus (LGN). The cells of the model receive strong (nonlinear) lateral inhibition from other neurons in the model cortex. Mathematical analysis of the dependence of membrane potential on synaptic conductances, and computer simulations, reveal that the nonlinearity of corticocortical inhibition cancels the nonlinear excitatory input from the LGN. This interaction produces linearized responses that agree with both extracellular and intracellular measurements. The model correctly accounts for experimental results about the time course of simple cell responses and also generates testable predictions about variation in linearity with position in the cortex, and the effect on the linearity of signal summation, caused by unbalancing the relative strengths of excitation and inhibition pharmacologically or with extrinsic current.

Muscarinic regulation of dendritic and axonal outputs of rat thalamic interneurons: a new cellular mechanism for uncoupling distal dendrites

Inhibition is crucial for sharpening the sensory information relayed through the thalamus. To understand how the interneuron-mediated inhibition in the thalamus is regulated, we studied the muscarinic effects on interneurons in the lateral posterior nucleus and lateral geniculate nucleus of the thalamus. Here, we report that activation of muscarinic receptors switched the firing pattern in thalamic interneurons from bursting to tonic. Although neuromodulators switch the firing mode in several other types of neurons by altering their membrane potential, we found that activation of muscarinic subtype 2 receptors switched the fire mode in thalamic interneurons by selectively decreasing their input resistance. This is attributable to the muscarinic enhancement of a hyperpolarizing potassium conductance and two depolarizing cation conductances. The decrease in input resistance appeared to electrotonically uncouple the distal dendrites of thalamic interneurons, which effectively changed the inhibition pattern in thalamocortical cells. These results suggest a novel cellular mechanism for the cholinergic transformation of long-range, slow dendrite- and axon-originated inhibition into short-range, fast dendrite-originated inhibition in the thalamus observed in vivo. It is concluded that the electrotonic properties of the dendritic compartments of thalamic interneurons can be dynamically regulated by muscarinic activity.

Membrane potential and conductance changes underlying length tuning of cells in cat primary visual cortex

Spike responses for many cells of cat primary visual cortex are optimized for the length of a drifting grating stimulus. Stimuli that are longer or shorter than this optimal length elicit submaximal spike responses. To investigate the mechanisms responsible for this length tuning, we have recorded intracellularly from visual cortical neurons in the cat while presenting drifting grating stimuli of varying lengths. We have found that the membrane potential responses of the cells also exhibit length tuning, but that the suppression of spike responses at lengths longer than the preferred is 30-50% stronger than the corresponding suppression of the membrane potential responses. This difference may be attributed to the effects of spike threshold. Furthermore, using steady injected currents, we have measured changes in the excitatory and inhibitory components of input conductance evoked by stimuli of different lengths. We find that, compared with optimal stimuli, long stimuli evoke both an increase in inhibitory conductance and a decrease in excitatory conductance. These two mechanisms differ in their contrast sensitivity, resulting in stronger end stopping and shorter optimal lengths for high-contrast stimuli. These patterns suggest that response suppression for long stimuli is generated by a combination of active inhibition from stimuli outside the excitatory receptive field, as well as decreased excitation from other cortical cells that are themselves end-inhibited.