Resonances and noise in a stochastic Hindmarsh-Rose model of thalamic neurons

Thalamic neurons exhibit subthreshold resonance when stimulated with small sine wave signals of varying frequency and stochastic resonance when noise is added to these signals. We study a stochastic Hindmarsh-Rose model using Monte-Carlo simulations to investigate how noise, in conjunction with subthreshold resonance, leads to a preferred frequency in the firing pattern. The resulting stochastic resonance (SR) exhibits a preferred firing frequency that is approximately exponential in its dependence on the noise amplitude. In similar experiments, frequency dependent SR is found in the reliability of detection of alpha-function inputs under noise, which are more realistic inputs for neurons. A mathematical analysis of the equations reveals that the frequency preference arises from the dynamics of the slow variable. Noise can then transfer the resonance over the firing threshold because of the proximity of the fast subsystem to a Hopf bifurcation point. Our results may have implications for the behavior of thalamic neurons in a network, with noise switching the membrane potential between different resonance modes.     

Respiratory rhythmicity in the cat.

Brain stem respiratory neuron activity in the cat was studied in relation to efferent outflow (phrenic discharge) under the influence of several forcing inputs: 1) CO2 tension: hypocapnia produces disappearance of firing in some neurons, and conversion of respiratory-modulated to continuous (tonic) firing in others. 2) Lung inflation: during the Bruer-Hering reflex, some neurons have "classical" responses and others have "paradoxical" responses (i.e., opposite in direction to peripheral discharge). 3) Electrical stimulation: stimulus trains to the pneumotaxic center region (rostral lateral pons) produce phase-switching, whose threshold is: a) sharp (indicating action of positive-feedback mechanisms), and b) dependent on timing of stimulus delivery (indicating continuous excitability changes during each respiratory phase). Auto- and crosscorrelation analysis revealed the existence of short-term interactions between: a) medullary inspiratory (I) neurons and phrenic motoneurons; b) pairs of medullary I neurons; c) medullary I neurons and expiratory (E) neurons. A model of the respiratory oscillator is presented, in which the processes of conversion of tonic to phasic activity and switching of the respiratory phases are explained by recurrent excitatory and inhibitory loops.     

Intrinsic membrane properties and dynamics of medial vestibular neurons: a simulation

The vestibulo-ocular and vestibulo-spinal network provides the ability to hold gaze fixed on an object during passive head movement. Within that network, most of the second-order neurons of the medial vestibular nucleus (MVNn) compute internal representations of head movement velocity in the horizontal plane. Our previous in vitro studies of the MVNn membrane properties indicated that they may play a major role in determining the dynamic properties of these neurons independently of their connectivity. The present study investigated that hypothesis at a theoretical level. Biophysical models of type A and B MVNn were developed. Two factors were found to be important in modeling tonic and phasic firing activity: the activation of the delayed potassium current and the rate of calcium flux. In addition, the model showed that the strength of the delayed potassium current may determine the different forms of action potentials observed experimentally. These two models (type A and B cells) were examined using depolarizing stimulation, random noise, step, ramp and sinusoidal inputs. For random noise, type A cells showed stable (regular) firing frequencies, while type B cells exhibited irregular activity. With step stimulation, the models exhibited tonic and phasic firing responses, respectively. Using ramp stimulations, frequency versus current curves showed a linear response for the type B neuron model. Finally, with sinusoidal stimulation of increasing frequencies, the type A model demonstrated a decrease in sensitivity, while the type B model exhibited an increase in sensitivity. These theoretical results support the hypothesis that MVNn intrinsic membrane properties specify various types of dynamic properties amongst these cells and therefore contribute to the wide range of dynamic responses which characterize the vestibulo-ocular and vestibulo-spinal network. Received: 1 August 1996 / Accepted in revised form: 16 December 1998     

Analysis of single unit activity evoked by tones amplitude-modulated with low-frequency noise in frog medulla

A method of constructing shuffled autocorrelation functions (SACF) was used to characterize single units in the dorsal medullar nucleus of the common frog (Rana temporaria). A continuous characteristic frequency tone modulated by repeating pieces of low-frequency noise was used as a stimulus. SACF was calculated as the correlation between the firing discharges evoked by different repeating pieces of the low-frequency noise. This approach obviates the influence of refractoriness and also considerably increases the sample representativity. Comparison of the SACF with the conventional ACF permits estimating the temporal dynamics of changes in the postspike excitability of the neuron. Analysis of several examples demonstrates the possibility of facilitation just after the period of absolute refractoriness in some tonic units. Neurons exhibiting only a phasic response to the onset of nonmodulated voice-frequency pieces were able to selectively respond to special moments of noise amplitude modulation. These cells demonstrate extremely high synchronism of reaction. We also describe a neuron characterized by an intrinsic periodicity of firing not connected with the dynamics of arriving stimuli.     

蝎毒耐热蛋白对大鼠急性分离海马神经元兴奋性的影响

应用全细胞膜片钳记录技术在电流钳模式下观察经持续高温等特殊处理后分离纯化的30～50 kDa蝎毒耐热蛋白(scorpion venom heat resistant protein,SVHRP)(国家发明专利,专利号ZL01 106166.92)对急性分离大鼠海马神经元兴奋性的影响.结果发现SVHRP可致海马神经元兴奋性降低.神经元经1×10-2 μg/mL SVHRP处理后动作电位发放模式改变,发放频率减少.在52个受检细胞中,有45个细胞产生位相放电(占86.54%);7个细胞产生重复放电(占13.46%).在产生位相放电的45个细胞中,有8个细胞在SVHRP处理后仍可以诱发出位相放电(占17.78%);37个细胞在SVHRP处理后无法诱导出位相放电(占82.22%),SVHRP处理后动作电位的产生与处理前相比,有显著差异(P＜0.01,n=45);在产生重复放电的7个细胞中,在1×10-2μg/mL SVHRP作用后均不能再次诱发出重复放电,而是产生一个动作电位或不再产生动作电位,药物处理前产生的动作电位个数为14.57±1.00,SVHRP处理后产生动作电位的个数为0.57±0.20,二者之间有显著性差异(P＜0.01,n=7).1×10-4 μg/mLSVHRP处理后,诱发动作电位产生的基强度由(75.10±8.99)pA增加到(119.85±12.73)pA(P＜0.01,n=8);阈电位由(-41.17±2.15)mV升至(-32.40±1.48)mV(P＜0.01,n=8);动作电位峰值由(68.49±2.33)mV下降至(54.71±0.81)mV(P＜0.01,n=8).由于神经元超兴奋性被认为是癫痫发作的基本机制之一,因此上述结果表明SVHRP有可能通过降低海马神经元兴奋性发挥其抗癫痫作用,这为蝎毒药物的进一步开发提供理论依据.     

Effects of chronic cardiac decentralization on functional properties of canine intracardiac neurons in vitro

Although intrinsic cardiac neurons display ongoing activity after chronic interruption of extrinsic autonomic inputs to the heart, the effects of decentralization on individual neurons remain unknown. The objective of this study was to determine the effects of chronic (3-4 wk) surgical decentralization on intracellular properties of, and neurotransmission among, neurons contained within the canine intrinsic right atrial ganglionated plexus in vitro. Properties of neurons from decentralized hearts were compared with those of neurons from sham-operated hearts (controls). Two populations of neurons were identified by their firing behavior in response to intracellular current injection. Fifty-nine percent of control neurons and 72% of decentralized neurons were phasic (discharged one action potential on excitation). Forty-one percent of control neurons and 27% of decentralized neurons were accommodating (multiple discharge with decrementing frequency). After chronic decentralization, input resistance of phasic neurons increased, whereas the duration of afterhyperpolarization of accommodating neurons decreased. Postsynaptic responses to interganglionic nerve stimulation were evoked in 89% of control neurons and 83% of decentralized neurons; the majority of these responses involved nicotinic receptors. These results show that, after chronic decentralization, intrinsic cardiac neurons 1) undergo changes in membrane properties that may lead to increased excitability while 2) maintaining synaptic neurotransmission within the intrinsic cardiac ganglionated plexus.     

Excitability of jcBNST Neurons Is Reduced in Alcohol-Dependent Animals during Protracted Alcohol Withdrawal

Alcohol dependence and withdrawal has been shown to cause neuroadaptive changes at multiple levels of the nervous system. At the neuron level, adaptations of synaptic connections have been extensively studied in a number of brain areas and accumulating evidence also shows the importance of alcohol dependence-related changes in the intrinsic cellular properties of neurons. At the same time, it is still largely unknown how such neural adaptations impact the firing and integrative properties of neurons. To address these problems, here, we analyze physiological properties of neurons in the bed nucleus of stria terminalis (jcBNST) in animals with a history of alcohol dependence. As a comprehensive approach, first we measure passive and active membrane properties of neurons using conventional current clamp protocols and then analyze their firing responses under the action of simulated synaptic bombardment via dynamic clamp. We find that most physiological properties as measured by DC current injection are barely affected during protracted withdrawal. However, neuronal excitability as measured from firing responses under simulated synaptic inputs with the dynamic clamp is markedly reduced in all 3 types of jcBNST neurons. These results support the importance of studying the effects of alcohol and drugs of abuse on the firing properties of neurons with dynamic clamp protocols designed to bring the neurons into a high conductance state. Since the jcBNST integrates excitatory inputs from the basolateral amygdala (BLA) and cortical inputs from the infralimbic and the insular cortices and in turn is believed to contribute to the inhibitory input to the central nucleus of the amygdala (CeA) the reduced excitability of the jcBNST during protracted withdrawal in alcohol-dependent animals will likely affect ability of the jcBNST to shape the activity and output of the CeA.     

Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs

Activity-dependent regulation of intrinsic excitability has been shown to greatly contribute to the overall plasticity of neuronal circuits. Such neuroadaptations are commonly investigated in patch clamp experiments using current step stimulation and the resulting input-output functions are analyzed to quantify alterations in intrinsic excitability. However, it is rarely addressed, how such changes translate to the function of neurons when they operate under natural synaptic inputs. Still, it is reasonable to expect that a strong correlation and near proportional relationship exist between static firing responses and those evoked by synaptic drive. We challenge this view by performing a high-yield electrophysiological analysis of cultured mouse hippocampal neurons using both standard protocols and simulated synaptic inputs via dynamic clamp. We find that under these conditions the neurons exhibit vastly different firing responses with surprisingly weak correlation between static and dynamic firing intensities. These contrasting responses are regulated by two intrinsic K-currents mediated by Kv1 and K_ir channels, respectively. Pharmacological manipulation of the K-currents produces differential regulation of the firing output of neurons. Static firing responses are greatly increased in stuttering type neurons under blocking their Kv1 channels, while the synaptic responses of the same neurons are less affected. Pharmacological blocking of K_ir-channels in delayed firing type neurons, on the other hand, exhibit the opposite effects. Our subsequent computational model simulations confirm the findings in the electrophysiological experiments and also show that adaptive changes in the kinetic properties of such currents can even produce paradoxical regulation of the firing output.     

Comparison of Coding Capabilities of Type I and Type II Neurons

We consider the dependence of information transfer by neurons on the Type I vs. Type II classification of their dynamics. Our computational study is based on Type I and II implementations of the Morris-Lecar model. It mainly concerns neurons, such as those in the auditory or electrosensory system, which encode band-limited amplitude modulations of a periodic carrier signal, and which fire at random cycles yet preferred phases of this carrier. We first show that the Morris-Lecar model with additive broadband noise ("synaptic noise") can exhibit such firing patterns with either Type I or II dynamics, with or without amplitude modulations of the carrier. We then compare the encoding of band-limited random amplitude modulations for both dynamical types. The comparison relies on a parameter calibration that closely matches firing rates for both models across a range of parameters. In the absence of synaptic noise, Type I performs slightly better than Type II, and its performance is optimal for perithreshold signals. However, Type II performs well over a slightly larger range of inputs, and this range lies mostly in the subthreshold region. Further, Type II performs marginally better than Type I when synaptic noise, which yields more realistic baseline firing patterns, is present in both models. These results are discussed in terms of the tuning and phase locking properties of the models with deterministic and stochastic inputs.     

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.     

Reliable Activation of Immature Neurons in the Adult Hippocampus

Neurons born in the adult dentate gyrus develop, mature, and connect over a long interval that can last from six to eight weeks. It has been proposed that, during this period, developing neurons play a relevant role in hippocampal signal processing owing to their distinctive electrical properties. However, it has remained unknown whether immature neurons can be recruited into a network before synaptic and functional maturity have been achieved. To address this question, we used retroviral expression of green fluorescent protein to identify developing granule cells of the adult mouse hippocampus and investigate the balance of afferent excitation, intrinsic excitability, and firing behavior by patch clamp recordings in acute slices. We found that glutamatergic inputs onto young neurons are significantly weaker than those of mature cells, yet stimulation of cortical excitatory axons elicits a similar spiking probability in neurons at either developmental stage. Young neurons are highly efficient in transducing ionic currents into membrane depolarization due to their high input resistance, which decreases substantially in mature neurons as the inward rectifier potassium (Kir) conductance increases. Pharmacological blockade of Kir channels in mature neurons mimics the high excitability characteristic of young neurons. Conversely, Kir overexpression induces mature-like firing properties in young neurons. Therefore, the differences in excitatory drive of young and mature neurons are compensated by changes in membrane excitability that render an equalized firing activity. These observations demonstrate that the adult hippocampus continuously generates a population of highly excitable young neurons capable of information processing.     

Influence of antigen on membrane properties of guinea pig bronchial ganglion neurons.

The bronchus was isolated from actively sensitized guinea pigs, and the effect of antigen challenge on the excitability of bronchial parasympathetic ganglion neurons was examined with standard intracellular recording techniques. Based on histological examination, we found that mast cells were located near parasympathetic ganglia neurons. Antigen challenge resulted in a loss of mast cell staining and the release of the mast cell-associated mediators, histamine (38 ng/g, approximately 14% of total content) and prostaglandin D2 (PGD2, 118 ng/g wet weight of tissue). Challenging the isolated bronchus with the sensitizing antigen resulted in a transient depolarization (mean 6 mV) of the resting membrane potential of the neurons. Antigen challenge also had a dramatic effect on the accommodative properties of the neurons. Before antigen challenge, two subpopulations of neurons could be differentiated by their response to cathodal current steps: 60% of the cells responded in a "phasic" manner, firing one to six spikes and then accommodated, whereas the balance fired spikes repetitively throughout the current pulse. In phasic firing cells, ovalbumin challenge produced a decrease in accommodation. This was evidenced by a fivefold increase in the number of action potentials elicited during a 500-ms suprathreshold current pulse. The antigen-induced depolarization could be mimicked by histamine, whereas the decrease in accommodation was mimicked by application of PGD2. Leukotriene C4, another mast cell-associated mediator, had no effect on these neuronal properties. These results provide evidence that the immediate hypersensitivity response in guinea pig airways may involve changes in membrane characteristics of bronchial parasympathetic ganglia neurons.     

Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity

Many neurons possess dendrites enriched with sodium channels and are capable of generating action potentials. However, the role of dendritic sodium spikes remain unclear. Here, we study computational models of neurons to investigate the functional effects of dendritic spikes. In agreement with previous studies, we found that point neurons or neurons with passive dendrites increase their somatic firing rate in response to the correlation of synaptic bombardment for a wide range of input conditions, i.e. input firing rates, synaptic conductances, or refractory periods. However, neurons with active dendrites show the opposite behavior: for a wide range of conditions the firing rate decreases as a function of correlation. We found this property in three types of models of dendritic excitability: a Hodgkin-Huxley model of dendritic spikes, a model with integrate and fire dendrites, and a discrete-state dendritic model. We conclude that fast dendritic spikes confer much broader computational properties to neurons, sometimes opposite to that of point neurons.     

An ephaptic transmission model of CA3 pyramidal cells: an investigation into electric field effects

Extracellular electric fields existing throughout the living brain affect the neural coding and information processing via ephaptic transmission, independent of synapses. A two-compartment whole field effect model (WFEM) of pyramidal neurons embedded within a resistive array which simulates the extracellular medium i.e. ephapse is developed to study the effects of electric field on neuronal behaviors. We derive the two linearized filed effect models (LFEM-1 and LFEM-2) from WFEM at the stable resting state. Through matching these simplified models to the subthreshold membrane response in experiments of the resting pyramidal cells exposed to applied electric fields, we not only verify our proposed model’s validity but also found the key parameters which dominate subthreshold frequency response characteristic. Moreover, we find and give its underlying biophysical mechanism that the unsymmetrical properties of active ion channels results in the very different low-frequency response of somatic and dendritic compartments. Following, WFEM is used to investigate both direct-current (DC) and alternating-current field effect on the neural firing patterns by bifurcation analyses. We present that DC electric field could modulate neuronal excitability, with the positive field improving the excitability, the modest negative field suppressing the excitability, but interestingly, the larger negative field re-exciting the neuron back into spiking behavior. The neuron exposed to the sinusoidal electric field exhibits abundant firing patterns sensitive to the input frequency and intensity. In addition, the electrical properties of ephapse can modulate the efficacy of field effect. Our simulated results are qualitatively in line with the relevant experimental results and can explain some experimental phenomena. Furthermore, they are helpful to provide the predictions which can be tested in future experiments.     

Mathematical models of cochlear nucleus onset neurons: I. Point neuron with many weak synaptic inputs

The cochlear nucleus (CN) presents a unique opportunity for quantitatively studying input-output transformations by neurons because it gives rise to a variety of different response types from a relatively homogeneous input source, the auditory nerve (AN). Particularly interesting among CN neurons are Onset (On) neurons, which have a prominent response to the onset of sustained sounds followed by little or no response in the steady-state. On neurons contrast sharply with their AN inputs, which respond vigorously throughout stimuli. On neurons can entrain to stimuli (firing once per cycle of a periodic stimulus) at up to 1000 Hz, unlike their AN inputs. To understand the mechanisms underlying these response patterns, we tested whether an integrate-to-threshold point-neuron model with a fixed refractory period can account for On discharge patterns for tones, systematically examining the effect of membrane time constant and the number and strength of the exclusively excitatory AN synaptic inputs. To produce both onset responses to high-frequency tone bursts and entrainment to a broad range of low-frequency tones, the model must have a short time constant (0.125 ms) and a large number (>100) of weak synaptic inputs, properties that are consistent with the electrical properties and anatomy of On-responding cells. With these parameters, the model acts like a coincidence detector with a threshold-like relationship between the instantaneous discharge rates of the output and the inputs. Onset responses to high-frequency tone bursts result because the threshold effect enhances the initial response of the AN inputs and suppresses their relatively lower sustained response. However, when the model entrains across a broad range of frequencies, it also produces short interspike intervals at the onset of high-frequency tone bursts, a response pattern not found in all types of On neurons. These results show a tradeoff, that may be a general property of many neurons, between following rapid stimulus fluctuations and responding without short interspike intervals at the onset of sustained stimuli.     

A model for repetitive firing in neurons

This paper describes a model for the generation of repetitive firing patterns in single neurons to be used as a module in large-scale network simulation studies. The model is based on the combination of extended versions of Hill's model for accomodation and of Kernell's model for adaptation. Both digital computer and electronic circuit realizations of the model are presented. The model is shown to produce strength-duration curves for accomodation which are compatible with available data from real neurons. Both “high ceiling” and “low ceiling” cell types can be matched by adjusting parameters in the model. An equation relating steady-state firing rate to amplitude of applied steady current is presented which includes the accumulation of potassium conductance changes with repetitive firing. The occurence of phasic and tonic responses to step stimulation is mapped in the parameter space of the model. Several representative response patterns to irregular inputs are presented.     

Transient Responses to Rapid Changes in Mean and Variance in Spiking Models

The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode.     

Noise enhances subthreshold oscillations in injured primary sensory neurons

Noise can play a constructive role in the detection of weak signals in various kinds of peripheral receptors and neurons. What the mechanism underlying the effect of noise is remains unclear. Here, the perforated patch-clamp technique was used on isolated cells from chronic compression of the dorsal root ganglion (DRG) model. Our data provided new insight indicating that, under conditions without external signals, noise can enhance subthreshold oscillations, which was observed in a certain type of neurons with high-frequency (20-100 Hz) intrinsic resonance from injured DRG neurons. The occurrence of subthreshold oscillation considerably decreased the threshold potential for generating repetitive firing. The above effects of noise can be abolished by blocking the persistent sodium current (I(Na, P)). Utilizing a mathematical neuron model we further simulated the effect of noise on subthreshold oscillation and firing, and also found that noise can enhance the electrical activity through autonomous stochastic resonance. Accordingly, we propose a new concept of the effects of noise on neural intrinsic activity, which suggests that noise may be an important factor for modulating the excitability of neurons and generation of chronic pain signals.     

After-hyperpolarization currents and acetylcholine control sigmoid transfer functions in a spiking cortical model

Recurrent networks are ubiquitous in the brain, where they enable a diverse set of transformations during perception, cognition, emotion, and action. It has been known since the 1970’s how, in rate-based recurrent on-center off-surround networks, the choice of feedback signal function can control the transformation of input patterns into activity patterns that are stored in short term memory. A sigmoid signal function may, in particular, control a quenching threshold below which inputs are suppressed as noise and above which they may be contrast enhanced before the resulting activity pattern is stored. The threshold and slope of the sigmoid signal function determine the degree of noise suppression and of contrast enhancement. This article analyses how sigmoid signal functions and their shape may be determined in biophysically realistic spiking neurons. Combinations of fast, medium, and slow after-hyperpolarization (AHP) currents, and their modulation by acetylcholine (ACh), can control sigmoid signal threshold and slope. Instead of a simple gain in excitability that was previously attributed to ACh, cholinergic modulation may cause translation of the sigmoid threshold. This property clarifies how activation of ACh by basal forebrain circuits, notably the nucleus basalis of Meynert, may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract information, as predicted by Adaptive Resonance Theory.     

Coexistence of lateral and co-tuned inhibitory configurations in cortical networks

The responses of neurons in sensory cortex depend on the summation of excitatory and inhibitory synaptic inputs. How the excitatory and inhibitory inputs scale with stimulus depends on the network architecture, which ranges from the lateral inhibitory configuration where excitatory inputs are more narrowly tuned than inhibitory inputs, to the co-tuned configuration where both are tuned equally. The underlying circuitry that gives rise to lateral inhibition and co-tuning is yet unclear. Using large-scale network simulations with experimentally determined connectivity patterns and simulations with rate models, we show that the spatial extent of the input determined the configuration: there was a smooth transition from lateral inhibition with narrow input to co-tuning with broad input. The transition from lateral inhibition to co-tuning was accompanied by shifts in overall gain (reduced), output firing pattern (from tonic to phasic) and rate-level functions (from non-monotonic to monotonically increasing). The results suggest that a single cortical network architecture could account for the extended range of experimentally observed response types between the extremes of lateral inhibitory versus co-tuned configurations.