Lateral sharpening of cortical frequency tuning by approximately balanced inhibition

Cortical inhibition plays an important role in shaping neuronal processing. The underlying synaptic mechanisms remain controversial. Here, in vivo whole-cell recordings from neurons in the rat primary auditory cortex revealed that the frequency tuning curve of inhibitory input was broader than that of excitatory input. This results in relatively stronger inhibition in frequency domains flanking the preferred frequencies of the cell and a significant sharpening of the frequency tuning of membrane responses. The less selective inhibition can be attributed to a broader bandwidth and lower threshold of spike tonal receptive field of fast-spike inhibitory neurons than nearby excitatory neurons, although both types of neurons receive similar ranges of excitatory input and are organized into the same tonotopic map. Thus, the balance between excitation and inhibition is only approximate, and intracortical inhibition with high sensitivity and low selectivity can laterally sharpen the frequency tuning of neurons, ensuring their highly selective representation.     

The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.     

Target and temporal pattern selection at neocortical synapses

We attempt to summarize the properties of cortical synaptic connections and the precision with which they select their targets in the context of information processing in cortical circuits. High-frequency presynaptic bursts result in rapidly depressing responses at most inputs onto spiny cells and onto some interneurons. These 'phasic' connections detect novelty and changes in the firing rate, but report frequency of maintained activity poorly. By contrast, facilitating inputs to interneurons that target dendrites produce little or no response at low frequencies, but a facilitating-augmenting response to maintained firing. The neurons activated, the cells they in turn target and the properties of those synapses determine which parts of the circuit are recruited and in what temporal pattern. Inhibitory interneurons provide both temporal and spatial tuning. The 'forward' flow from layer-4 excitatory neurons to layer 3 and from 3 to 5 activates predominantly pyramids. 'Back' projections, from 3 to 4 and 5 to 3, do not activate excitatory cells, but target interneurons. Despite, therefore, an increasing complexity in the information integrated as it is processed through these layers, there is little 'contamination' by 'back' projections. That layer 6 acts both as a primary input layer feeding excitation 'forward' to excitatory cells in other layers and as a higher-order layer with more integrated response properties feeding inhibition to layer 4 is discussed.     

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids

The visual response of a cell in the primary visual cortex (V1) to a drifting grating stimulus at the cell’s preferred orientation decreases when a second, perpendicular, grating is superimposed. This effect is called masking. To understand the nonlinear masking effect, we model the response of Macaque V1 simple cells in layer 4Cα to input from magnocellular Lateral Geniculate Nucleus (LGN) cells. The cortical model network is a coarse-grained reduction of an integrate-and-fire network with excitation from LGN input and inhibition from other cortical neurons. The input is modeled as a sum of LGN cell responses. Each LGN cell is modeled as the convolution of a spatio-temporal filter with the visual stimulus, normalized by a retinal contrast gain control, and followed by rectification representing the LGN spike threshold. In our model, the experimentally observed masking arises at the level of LGN input to the cortex. The cortical network effectively induces a dynamic threshold that forces the test grating to have high contrast before it can overcome the masking provided by the perpendicular grating. The subcortical nonlinearities and the cortical network together account for the masking effect. Melinda Koelling is formerly from Center for Neural Science and Courant Institute, New York University.     

Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways

The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit.     

The Role of Thalamic Population Synchrony in the Emergence of Cortical Feature Selectivity

In a wide range of studies, the emergence of orientation selectivity in primary visual cortex has been attributed to a complex interaction between feed-forward thalamic input and inhibitory mechanisms at the level of cortex. Although it is well known that layer 4 cortical neurons are highly sensitive to the timing of thalamic inputs, the role of the stimulus-driven timing of thalamic inputs in cortical orientation selectivity is not well understood. Here we show that the synchronization of thalamic firing contributes directly to the orientation tuned responses of primary visual cortex in a way that optimizes the stimulus information per cortical spike. From the recorded responses of geniculate X-cells in the anesthetized cat, we synthesized thalamic sub-populations that would likely serve as the synaptic input to a common layer 4 cortical neuron based on anatomical constraints. We used this synchronized input as the driving input to an integrate-and-fire model of cortical responses and demonstrated that the tuning properties match closely to those measured in primary visual cortex. By modulating the overall level of synchronization at the preferred orientation, we show that efficiency of information transmission in the cortex is maximized for levels of synchronization which match those reported in thalamic recordings in response to naturalistic stimuli, a property which is relatively invariant to the orientation tuning width. These findings indicate evidence for a more prominent role of the feed-forward thalamic input in cortical feature selectivity based on thalamic synchronization.     

Optogenetic Stimulation of the Corticothalamic Pathway Affects Relay Cells and GABAergic Neurons Differently in the Mouse Visual Thalamus

The dorsal lateral geniculate nucleus (dLGN) serves as the primary conduit of retinal information to visual cortex. In addition to retinal input, dLGN receives a large feedback projection from layer VI of visual cortex. Such input modulates thalamic signal transmission in different ways that range from gain control to synchronizing network activity in a stimulus-specific manner. However, the mechanisms underlying such modulation have been difficult to study, in part because of the complex circuitry and diverse cell types this pathway innervates. To address this and overcome some of the technical limitations inherent in studying the corticothalamic (CT) pathway, we adopted a slice preparation in which we were able to stimulate CT terminal arbors in the visual thalamus of the mouse with blue light by using an adeno-associated virus to express the light-gated ion channel, ChIEF, in layer VI neurons. To examine the postsynaptic responses evoked by repetitive CT stimulation, we recorded from identified relay cells in dLGN, as well as GFP expressing GABAergic neurons in the thalamic reticular nucleus (TRN) and intrinsic interneurons of dLGN. Relay neurons exhibited large glutamatergic responses that continued to increase in amplitude with each successive stimulus pulse. While excitatory responses were apparent at postnatal day 10, the strong facilitation noted in adult was not observed until postnatal day 21. GABAergic neurons in TRN exhibited large initial excitatory responses that quickly plateaued during repetitive stimulation, indicating that the degree of facilitation was much larger for relay cells than for TRN neurons. The responses of intrinsic interneurons were smaller and took the form of a slow depolarization. These differences in the pattern of excitation for different thalamic cell types should help provide a framework for understanding how CT feedback alters the activity of visual thalamic circuitry during sensory processing as well as different behavioral or pathophysiological states.     

Parallel regulation of feedforward inhibition and excitation during whisker map plasticity

Sensory experience drives robust plasticity of sensory maps in cerebral cortex, but the role of inhibitory circuits in this process is not fully understood. We show that classical deprivation-induced whisker map plasticity in layer 2/3 (L2/3) of rat somatosensory (S1) cortex involves robust weakening of L4-L2/3 feedforward inhibition. This weakening was caused by reduced L4 excitation onto L2/3 fast-spiking (FS) interneurons, which mediate sensitive feedforward inhibition and was partially offset by strengthening of unitary FS to L2/3 pyramidal cell synapses. Weakening of feedforward inhibition paralleled the known weakening of feedforward excitation. As a result, mean excitation-inhibition balance and timing onto L2/3 pyramidal cells were preserved. Thus, reduced feedforward inhibition is a covert compensatory process that can maintain excitatory-inhibitory balance during classical deprivation-induced Hebbian map plasticity.     

Cre recombinase-mediated gene deletion in layer 4 of murine sensory cortical areas

Thalamocortical input to layer 4 carries the major ascending sensory information to the mammalian sensory cortex and is crucial for the function and plasticity of sensory cortical areas. Here we report identification of a Six3-cre transgene that is selectively expressed in layer 4 of sensory cortical areas but not in the thalamus. In the mature somatosensory cortex Cre recombinase expressed from the transgene is able to mediate gene deletion in the overwhelming majority of layer 4 neurons, including GABAergic interneurons. The gene deletion in layer 4 mainly occurs during the first postnatal week. This cre transgene therefore provides a useful tool for examining the role of proteins expressed in layer 4 neurons.     

Synaptic mechanisms underlying auditory processing

In vivo voltage clamp recordings have provided new insights into the synaptic mechanisms that underlie processing in the primary auditory cortex. Of particular importance are the discoveries that excitatory and inhibitory inputs have similar frequency and intensity tuning, that excitation is followed by inhibition with a short delay, and that the duration of inhibition is briefer than expected. These findings challenge existing models of auditory processing in which broadly tuned lateral inhibition is used to limit excitatory receptive fields and suggest new mechanisms by which inhibition and short term plasticity shape neural responses.     

Interval-counting neurons in the anuran auditory midbrain: factors underlying diversity of interval tuning

In anurans, the temporal patterning of sound pulses is the primary information used for differentiating between spectrally similar calls. One class of midbrain neurons, referred to as ‘interval-counting’ cells, appears to be particularly important for discriminating among calls that differ in pulse repetition rate (PRR). These cells only respond after several pulses are presented with appropriate interpulse intervals. Here we show that the range of selectivity and sharpness of interval tuning vary considerably across neurons. Whole-cell recordings revealed that neurons showing temporally summating excitatory postsynaptic potentials (EPSPs) with little or no inhibition or activity-dependent enhancement of excitation exhibited low-pass or band-pass tuning to slow PRRs. Neurons that showed inhibition and rate-dependent enhancement of excitation, however, were band-pass or high-pass to intermediate or fast PRRs. Surprisingly, across cells, interval tuning based on membrane depolarization and spike rate measures were not significantly correlated. Neurons that lacked inhibition showed the greatest disparities between these two measures of interval tuning. Cells that showed broad membrane potential-based tuning, for example, varied considerably in their spike rate-based tuning; narrow spike rate-based tuning resulted from ‘thresholding’ processes, whereby only the largest depolarizations triggered spikes. The potential constraints associated with generating interval tuning in this manner are discussed.     

The distribution of corticocortical, thalamocortical, and callosal inputs on identified motor cortex output neurons: mechanisms for their selective recruitment.

Motor cortex neurons were identified antidromically in anesthetized cats by their axonal projections to one of six targets: (1) somatosensory cortex, (2) opposite motor cortex, (3) red nucleus, (4) lateral reticular nucleus, (5) spinal cord, and (6) ventrolateral thalamus. Three inputs to motor cortex were tested for their influences on the identified cortical efferent neurons. The tested inputs originated from ipsilateral somatosensory cortex, opposite motor cortex, and ventral thalamus. Subthreshold effects of input pathways were detected by monitoring latency variations of antidromic responses. The three afferent sources, when activated by electrical stimulation, were not equally effective on motor cortex neurons. Ipsilateral corticocortical and thalamocortical excitation were found for the majority of neurons; the influenced proportions ranged from 55% to 100%, according to the target of the output neurons. Effects from the opposite hemisphere were found for only 5% to 30% of the neurons in the same projection classes. Many neurons (36 of 81, or 44%) were excited from more than one source, but few (5 of 37, or 14%) were influenced by all three possible sources of input, even in small regions of cortex innervated by all three of the inputs. Among 19 electrode tracks where all three inputs were present, there were only 2 tracks where all the neurons shared the same combination of inputs. Even for neurons in closest anatomical proximity ("clusters"), it was unusual (only 7 of 25 clusters) for all the neurons to have the same input pattern. Among the seven clusters where all the neurons shared the same input pattern, five of the clusters projected to the same target. These variable combinations of inputs to motor cortex neurons support the conclusion that efferent neurons could be recruited selectively from separate cortical layers or from within clusters of nearby neurons, according to the target of their axonal projection.     

Somatic evoked high-frequency magnetic oscillations reflect activity of inhibitory interneurons in the human somatosensory cortex

High-frequency potential oscillations in the range of 300–900 Hz have recently been shown to concur with the primary response (N20) of the somatosensory cortex in awake humans. However, the physiological mechanisms of the high-frequency oscillations remained undetermined. We addressed the issue by analyzing magnetic fields during wakefulness and sleep over the left hemisphere to right median nerve stimulation with a wide bandpass (0.1–2000 Hz) recording with subsequent high-pass (> 300 Hz) and low-pass (< 300 Hz) filtering. With wide bandpass recordings, high-frequency magnetic oscillations with the main signal energy at 580–780 Hz were superimposed on the N20m during wakefulness. Isofield mapping at each peak of the high-pass filtered and isolated high-frequency oscillations showed a dipolar pattern and the estimated source for these peaks was the primary somatosensory cortex (area 3b) very close to that for the N20m peak. During sleep, the high-frequency oscillations showed dramatic diminution in amplitude while the N20m amplitude exhibited a moderate increment. This reciprocal relation between the high-frequency oscillations and the N20m during a wake-sleep cycle suggests that they represent different generator substrates. We speculate that the high-frequency oscillations represent a localized activity of the GABAergic inhibitory interneurons of layer 4, which have been shown in animal experiments to respond monosynaptically to thalamo-cortical input with a high-frequency (600–900 Hz) burst of short duration spikes. On the other hand, the underlying N20m represents activity of pyramidal neurons which receive monosynaptic excitatory input from the thalamus as well as a feed-forward inhibition from the interneurons.     

Cortically-Controlled Population Stochastic Facilitation as a Plausible Substrate for Guiding Sensory Transfer across the Thalamic Gateway

The thalamus is the primary gateway that relays sensory information to the cerebral cortex. While a single recipient cortical cell receives the convergence of many principal relay cells of the thalamus, each thalamic cell in turn integrates a dense and distributed synaptic feedback from the cortex. During sensory processing, the influence of this functional loop remains largely ignored. Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. The synaptic bombardment of cortical origin was mimicked through the injection of a stochastic mixture of excitatory and inhibitory conductances, resulting in a gradable correlation level of afferent activity shared by thalamic cells. The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. This suggests that the transfer efficiency of relay cells could be selectively amplified when they become simultaneously desynchronized by the cortical feedback. When applied to the intact brain, this network regulation mechanism could direct an attentional focus to specific thalamic subassemblies and select the appropriate input lines to the cortex according to the descending influence of cortically-defined “priors”.     

Thoughts on the cerebral cortex

The cortex is often described as a network processing information in the direction from sensory to motor areas. However, the structure of the cortex is asymmetrical only in the vertical direction, suggesting an input-output transformation between layers rather than between areas. This operation must be a very generally applicable one, since the plan of the cortex is basically the same everywhere. In an attempt to understand it, a skeleton cortex of only pyramidal cells is considered. They are characterized by a double dendritic expansion, an apical one in the first layer, which is considered as the input layer, and a basal one which receives excitation from the axon collaterals of other pyramidal cells. If pyramidal cells learn (perhaps by growing dendritic spines) to respond to frequent constellations of activity in their afferents, each will learn a property of the input (through its apical dendrites) provided that it was preceded by other properties sensed by neighbouring pyramidal cells (which influences it through its basal dendrites). Thus the pyramidal cells will code the input in terms of properties which have a tendency to follow each other. This will be a coding which reflects the causal structure of the world. Various uses of a network embodying the conditional probabilities of events in the input are described, including recognition of familiar sequences and prediction. The local variation of fiber patterns in the cerebral cortex of man, described as myeloarchitectonics, is interpreted as a macroscopical expression of the different statistics of the set of conditional probabilities linking the events represented by individual pyramidal cells in different areas (in different functional contexts).     

The Distribution of Corticocortical,Thalamocortical, and Callosal Inputs on Identified Motor Cortex Output Neurons: Mechanisms for Their Selective Recruitment

Motor cortex neurons were identified antidromically in anesthetized cats by their axonal projections to one of six targets: (1) somatosensory cortex, (2) opposite motor cortex, (3) red nucleus, (4) lateral reticular nucleus, (5) spinal cord, and (6) ventrolateral thalamus. Three inputs to motor cortex were tested for their influences on the identified cortical efferent neurons. The tested inputs originated from ipsilateral somatosensory cortex, opposite motor cortex, and ventral thalamus. Subthreshold effects of input pathways were detected by monitoring latency variations of antidromic responses.

The three afferent sources, when activated by electrical stimulation, were not equally effective on motor cortex neurons. Ipsilateral corticocortical and thalamocortical excitation were found for the majority of neurons; the influenced proportions ranged from 55% to 100%, according to the target of the output neurons. Effects from the opposite hemisphere were found for only 5% to 30% of the neurons in the same projection classes.

Many neurons (36 of 81, or 44%) were excited from more than one source, but few (5 of 37, or 14%) were influenced by all three possible sources of input, even in small regions of cortex innervated by all three of the inputs. Among 19 electrode tracks where all three inputs were present, there were only 2 tracks where all the neurons shared the same combination of inputs. Even for neurons in closest anatomical proximity (“clusters”), it was unusual (only 7 of 25 clusters) for all the neurons to have the same input pattern. Among the seven clusters where all the neurons shared the same input pattern, five of the clusters projected to the same target. These variable combinations of inputs to motor cortex neurons support the conclusion that efferent neurons could be recruited selectively from separate cortical layers or from within clusters of nearby neurons, according to the target of their axonal projection.     

Thalamocortical inputs show post-critical-period plasticity

Experience-dependent plasticity in the adult brain has clinical potential for functional rehabilitation following central and peripheral nerve injuries. Here, plasticity induced by unilateral infraorbital (IO) nerve resection in 4-week-old rats was mapped using MRI and synaptic mechanisms were elucidated by slice electrophysiology. Functional MRI demonstrates a cortical potentiation compared to thalamus 2 weeks after IO nerve resection. Tracing thalamocortical (TC) projections with manganese-enhanced MRI revealed circuit changes in the spared layer 4 (L4) barrel cortex. Brain slice electrophysiology revealed TC input strengthening onto L4 stellate cells due to an increase in postsynaptic strength and the number of functional synapses. This work shows that the TC input is a site for robust plasticity after the end of the previously defined critical period for this input. Thus, TC inputs may represent a major site for adult plasticity in contrast to the consensus that adult plasticity mainly occurs at cortico-cortical connections.     

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.     

The role of the thalamus in the flow of information to the cortex

The lateral geniculate nucleus is the best understood thalamic relay and serves as a model for all thalamic relays. Only 5-10% of the input to geniculate relay cells derives from the retina, which is the driving input. The rest is modulatory and derives from local inhibitory inputs, descending inputs from layer 6 of the visual cortex, and ascending inputs from the brainstem. These modulatory inputs control many features of retinogeniculate transmission. One such feature is the response mode, burst or tonic, of relay cells, which relates to the attentional demands at the moment. This response mode depends on membrane potential, which is controlled effectively by the modulator inputs. The lateral geniculate nucleus is a first-order relay, because it relays subcortical (i.e. retinal) information to the cortex for the first time. By contrast, the other main thalamic relay of visual information, the pulvinar region, is largely a higher-order relay, since much of it relays information from layer 5 of one cortical area to another. All thalamic relays receive a layer-6 modulatory input from cortex, but higher-order relays in addition receive a layer-5 driver input. Corticocortical processing may involve these corticothalamocortical 're-entry' routes to a far greater extent than previously appreciated. If so, the thalamus sits at an indispensable position for the modulation of messages involved in corticocortical processing.     

Estimation of synaptic conductances.

In order to identify and understand mechanistically the cortical circuitry of sensory information processing estimates are needed of synaptic input fields that drive neurons. From intracellular in vivo recordings one would like to estimate net synaptic conductance time courses for excitation and inhibition, g(E)(t) and g(I)(t), during time-varying stimulus presentations. However, the intrinsic conductance transients associated with neuronal spiking can confound such estimates, and thereby jeopardize functional interpretations. Here, using a conductance-based pyramidal neuron model we illustrate errors in estimates when the influence of spike-generating conductances are not reduced or avoided. A typical estimation procedure involves approximating the current-voltage relation at each time point during repeated stimuli. The repeated presentations are done in a few sets, each with a different steady bias current. From the trial-averaged smoothed membrane potential one estimates total membrane conductance and then dissects out estimates for g(E)(t) and g(I)(t). Simulations show that estimates obtained during phases without spikes are good but those obtained from phases with spiking should be viewed with skeptism. For the simulations, we consider two different synaptic input scenarios, each corresponding to computational network models of orientation tuning in visual cortex. One input scenario mimics a push-pull arrangement for g(E)(t) and g(I)(t) and idealized as specified smooth time courses. The other is taken directly from a large-scale network simulation of stochastically spiking neurons in a slab of cortex with recurrent excitation and inhibition. For both, we show that spike-generating conductances cause serious errors in the estimates of g(E) and g(I). In some phases for the push-pull examples even the polarity of g(I) is mis-estimated, indicating significant increase when g(I) is actually decreased. Our primary message is to be cautious about forming interpretations based on estimates developed during spiking phases.