Temporal integration can readily switch between sublinear and supralinear summation

Temporal integration on the dendrites of fast-spiking basket cells

Neurons receive synaptic inputs with diverse temporal patterns in vivo, and their integration of these patterns is critical for understanding information processing mechanisms in the brain. Fast-spiking basket cells, which perform both supralinear and sublinear dendritic integration, are essential for inhibitory control in the hippocampus. However, their responses and the mechanisms underlying different temporal input patterns remain unclear. To address this question, we apply inputs with varying windows of time to a detailed compartmental model of basket cells. Our results reveal that when synaptic inputs are randomly dispersed, temporal integration in FS BCs exhibits a sigmoid-like response within the temporal window. In contrast, synchronous input protocols more effectively elicit action potentials, while asynchronous inputs generate more spikes in response to suprathreshold stimuli. Further analysis shows that the supralinear dendrites of fast-spiking basket cells primarily mediate this nonlinearity to asynchronous inputs, owing to their larger dendritic diameters. Moreover, we discover that delayed rectifier [Formula: see text] channels reduce sensitivity to synchronous inputs, whereas N-type [Formula: see text] channels enhance sensitivity to asynchronous inputs. These results provide insights into the mechanisms underlying the temporal coding of fast-spiking basket cells, which is crucial for understanding their role in neuronal oscillations.

Relative Contributions of Different Neural Sources to the EEG

Dogma dictates that the EEG signal is generated by postsynaptic currents (PSCs) because there are an enormous number of synapses in the brain, and PSCs have relatively long durations. However, PSCs are not the only potential source of electric fields in the brain. Action potentials, afterpolarizations, and presynaptic activity can also generate electric fields. Experimentally it is exceedingly difficult to delineate the contributions of different sources because they are casually linked. However, using computational modeling, we can interrogate the relative contributions of different neural elements to the EEG. We used a library of neuron models with morphologically realistic axonal arbors to quantify the relative contributions of PSCs, action potentials, and presynaptic activity to the EEG signal. Consistent with prior assertions, PSCs were the largest contributor to the EEG, but action potentials and afterpolarizations can also make appreciable contributions. For a population of neurons generating simultaneous PSCs and action potentials, we found that the action potentials accounted for up to 20% of the source strength while PSCs accounted for the other 80% and presynaptic activity negligibly contributed. Additionally, L5 PCs generated the largest PSC and action potential signals indicating that they the dominant EEG signal generator. Further, action potentials and afterpolarizations were sufficient to generate physiological oscillations, indicating that they are valid source contributors to the EEG. The EEG emerges from a combination of multiple different source, and, while PSCs are the largest contributor, other sources are non-negligible and should be included in modeling, analysis and interpretation of the EEG.

Nonlinear pulses at the interface and its relation to state and temperature

Environmental temperature has a well-conserved effect on the pulse velocity and excitability of excitable biological systems. The consistency suggests that the cause originates from a fundamental principle. A physical (hydrodynamic) approach has proposed that the thermodynamic state of the hydrated interface (e.g., plasma membrane) determines the pulse behavior. This implies that the temperature effect happens because the environmental temperature affects the state of the interface in any given system. To test the hypothesis, we measured temperature-dependent phase diagrams of a lipid monolayer and studied the properties of nonlinear acoustic pulses excited along the membrane. We observed that the membrane in the fluid-gel transition regime exhibited lower compressibility (i.e., stiffer) overall with increasing temperature. Nonlinear pulses excited near the transition state propagated with greater velocity with increasing temperature, and these observations were consistent with the compressibility profiles. Excitability was suppressed significantly or ceased completely when the state departed too far from the transition regime either by cooling or by heating. The overall correlation between the pulses in the membrane and in living systems as a function of temperature supports the view that the thermodynamic state of the interface and phase transition are the key to understanding pulse propagation in excitable systems.

Collision and annihilation of nonlinear sound waves and action potentials in interfaces

Nerve impulses, previously proposed as manifestations of nonlinear acoustic pulses localized at the plasma membrane, can annihilate upon collision. However, whether annihilation of acoustic waves at interfaces takes place is unclear. We previously showed the propagation of nonlinear sound waves that propagate as solitary waves above a threshold (super-threshold) excitation in a lipid monolayer near a phase transition. Here we investigate the interaction of these waves. Sound waves were excited mechanically via a piezo cantilever in a lipid monolayer at the air-water interface and their amplitude is reported before and after a collision. The compression amplitude was observed via Förster resonance energy transfer between donor and acceptor dyes, measured at fixed points along the propagation path in the lipid monolayer. We provide direct experimental evidence for the annihilation of two super-threshold interfacial pulses upon head-on collision in a lipid monolayer and conclude that sound waves propagating in a lipid interface can interact linearly, nonlinearly, or annihilate upon collision depending on the state of the system. Thus we show that the main characteristics of nerve impulses, i.e. solitary character, velocity, couplings, all-or-none behaviour, threshold and even annihilation are also demonstrated by nonlinear sound waves in a lipid monolayer, where they follow directly from the thermodynamic principles applied to an interface. As these principles are equally unavoidable in a nerve membrane, our observations strongly suggest that the underlying physical basis of action potentials and the observed nonlinear-pules is identical.

Injection of fully-defined signal mixtures: a novel high-throughput tool to study neuronal encoding and computations

Understanding of how neurons transform fluctuations of membrane potential, reflecting input activity, into spike responses, which communicate the ultimate results of single-neuron computation, is one of the central challenges for cellular and computational neuroscience. To study this transformation under controlled conditions, previous work has used a signal immersed in noise paradigm where neurons are injected with a current consisting of fluctuating noise that mimics on-going synaptic activity and a systematic signal whose transmission is studied. One limitation of this established paradigm is that it is designed to examine the encoding of only one signal under a specific, repeated condition. As a result, characterizing how encoding depends on neuronal properties, signal parameters, and the interaction of multiple inputs is cumbersome. Here we introduce a novel fully-defined signal mixture paradigm, which allows us to overcome these problems. In this paradigm, current for injection is synthetized as a sum of artificial postsynaptic currents (PSCs) resulting from the activity of a large population of model presynaptic neurons. PSCs from any presynaptic neuron(s) can be now considered as "signal", while the sum of all other inputs is considered as "noise". This allows us to study the encoding of a large number of different signals in a single experiment, thus dramatically increasing the throughput of data acquisition. Using this novel paradigm, we characterize the detection of excitatory and inhibitory PSCs from neuronal spike responses over a wide range of amplitudes and firing-rates. We show, that for moderately-sized neuronal populations the detectability of individual inputs is higher for excitatory than for inhibitory inputs during the 2-5 ms following PSC onset, but becomes comparable after 7-8 ms. This transient imbalance of sensitivity in favor of excitation may enhance propagation of balanced signals through neuronal networks. Finally, we discuss several open questions that this novel high-throughput paradigm may address.

Frequency-dependent signal processing in apical dendrites of hippocampal CA1 pyramidal cells

Depending on an animal's behavioral state, hippocampal CA1 pyramidal cells receive distinct patterns of excitatory and inhibitory synaptic inputs. The time-dependent changes in the frequencies of these inputs and the nonuniform distribution of voltage-gated channels lead to dynamic fluctuations in membrane conductance. In this study, using a whole-cell patch-clamp method, we attempted to record and analyze the frequency dependencies of membrane responsiveness in Wistar rat hippocampal CA1 pyramidal cells following noise current injection directly into dendrites and somata under pharmacological blockade of all synaptic inputs. To estimate the frequency-dependent properties of membrane potential, membrane impedance was determined from the voltage response divided by the input current in the frequency domain. The cell membrane of most neurons showed low-pass filtering properties in all regions. In particular, the properties were strongly expressed in the somata or proximal dendrites. Moreover, the data revealed nonuniform distribution of dendritic impedance, which was high in the intermediate segment of the apical dendritic shaft (∼220-260μm from the soma). The low-pass filtering properties in the apical dendrites were more enhanced by membrane depolarization than those in the somata. Coherence spectral analysis revealed high coherence between the input signal and the output voltage response in the theta-gamma frequency range, and large lags emerged in the distal dendrites in the gamma frequency range. Our results suggest that apical dendrites of hippocampal CA1 pyramidal cells integrate synaptic inputs according to the frequency components of the input signal along the dendritic segments receiving the inputs.

A unifying mechanistic model of selective attention in spiking neurons

Visuospatial attention produces myriad effects on the activity and selectivity of cortical neurons. Spiking neuron models capable of reproducing a wide variety of these effects remain elusive. We present a model called the Attentional Routing Circuit (ARC) that provides a mechanistic description of selective attentional processing in cortex. The model is described mathematically and implemented at the level of individual spiking neurons, with the computations for performing selective attentional processing being mapped to specific neuron types and laminar circuitry. The model is used to simulate three studies of attention in macaque, and is shown to quantitatively match several observed forms of attentional modulation. Specifically, ARC demonstrates that with shifts of spatial attention, neurons may exhibit shifting and shrinking of receptive fields; increases in responses without changes in selectivity for non-spatial features (i.e. response gain), and; that the effect on contrast-response functions is better explained as a response-gain effect than as contrast-gain. Unlike past models, ARC embodies a single mechanism that unifies the above forms of attentional modulation, is consistent with a wide array of available data, and makes several specific and quantifiable predictions.

At a given moment, a tremendous amount of visual information falls on the retinae, far more than the brain is capable of processing. By directing attention to a spatial location, stimuli at that position can be selectively processed, while irrelevant information from non-attended locations can be largely ignored. We present a detailed model that describes the mechanisms by which visual spatial attention may be implemented in the brain. Using this model, we simulated three previous studies of spatial attention in primates, and analysed the simulation data using the same methods as in the original experiments. Across these simulations, and without altering model parameters, our model produces results that are statistically indistinguishable from those recorded in primates. Unlike previous work, our model provides greater biological detail of how the brain performs selective visual processing, while also accurately demonstrating numerous forms of selective attention. Our results suggest that these seemingly different forms of attentional effects may result from a single mechanism for selectively processing attended stimuli.

Phenomenological incorporation of nonlinear dendritic integration using integrate-and-fire neuronal frameworks

It has been discovered recently in experiments that the dendritic integration of excitatory glutamatergic inputs and inhibitory GABAergic inputs in hippocampus CA1 pyramidal neurons obeys a simple arithmetic rule as V(S)(Exp) ≈ V(E)(Exp) + V(I)(Exp) + kV(E)(Exp) V(I)(Exp), where V(S)(Exp), V(E)(Exp) and V(I)(Exp) are the respective voltage values of the summed somatic potential, the excitatory postsynaptic potential (EPSP) and the inhibitory postsynaptic potential measured at the time when the EPSP reaches its peak value. Moreover, the shunting coefficient k in this rule only depends on the spatial location but not the amplitude of the excitatory or inhibitory input on the dendrite. In this work, we address the theoretical issue of how much the above dendritic integration rule can be accounted for using subthreshold membrane potential dynamics in the soma as characterized by the conductance-based integrate-and-fire (I&F) model. Then, we propose a simple I&F neuron model that incorporates the spatial dependence of the shunting coefficient k by a phenomenological parametrization. Our analytical and numerical results show that this dendritic-integration-rule-based I&F (DIF) model is able to capture many experimental observations and it also yields predictions that can be used to verify the validity of the DIF model experimentally. In addition, the DIF model incorporates the dendritic integration effects dynamically and is applicable to more general situations than those in experiments in which excitatory and inhibitory inputs occur simultaneously in time. Finally, we generalize the DIF neuronal model to incorporate multiple inputs and obtain a similar dendritic integration rule that is consistent with the results obtained by using a realistic neuronal model with multiple compartments. This generalized DIF model can potentially be used to study network dynamics that may involve effects arising from dendritic integrations.

In vivo voltage-dependent influences on summation of synaptic potentials in neurons of the lateral nucleus of the amygdala

The amygdala has a fundamental role in driving affective behaviors in response to sensory cues. To accomplish this, neurons of the lateral nucleus (LAT) must integrate a large number of synaptic inputs. A wide range of factors influence synaptic integration, including membrane potential, voltage-gated ion channels and GABAergic inhibition. However, little is known about how these factors modulate integration of synaptic inputs in LAT neurons in vivo. The purpose of this study was to determine the voltage-dependent factors that modify in vivo integration of synaptic inputs in the soma of LAT neurons. In vivo intracellular recordings from anesthetized rats were used to measure post-synaptic potentials (PSPs) and clusters of PSPs across a range of membrane potentials. These studies found that the relationship between membrane potential and PSP clusters was sublinear, due to a reduction of cluster amplitude and area at depolarized membrane potentials. In combination with intracellular delivery of pharmacological agents, it was found that the voltage-dependent suppression of PSP clusters was sensitive to tetraethylammonium (TEA), but not cesium or a blocker of fast GABAergic inhibition. These findings indicate that integration of PSPs in LAT neurons in vivo is strongly modified by somatic membrane potential, likely through voltage-dependent TEA-sensitive potassium channels. Conditions that lead to a shift in membrane potential, or a modulation of the number or function of these ion channels will lead to a more uniform capacity for integration across voltages, and perhaps greatly facilitate amygdala-dependent behaviors.

Integration of subthreshold and suprathreshold excitatory barrages along the somatodendritic axis of pyramidal neurons

Neurons integrate inputs arriving in different cellular compartments to produce action potentials that are transmitted to other neurons. Because of the voltage- and time-dependent conductances in the dendrites and soma, summation of synaptic inputs is complex. To examine summation of membrane potentials and firing rates, we performed whole-cell recordings from layer 5 cortical pyramidal neurons in acute slices of the rat's somatosensory cortex. We delivered subthreshold and suprathreshold stimuli at the soma and several sites on the apical dendrite, and injected inputs that mimic synaptic barrages at individual or distributed sites. We found that summation of subthreshold potentials differed from that of firing rates. Subthreshold summation was linear when barrages were small but became supralinear as barrages increased. When neurons were discharging repetitively the rules were more diverse. At the soma and proximal apical dendrite summation of the evoked firing rates was predominantly sublinear whereas in the distal dendrite summation ranged from supralinear to sublinear. In addition, the integration of inputs delivered at a single location differed from that of distributed inputs only for suprathreshold responses. These results indicate that convergent inputs onto the apical dendrite and soma do not simply summate linearly, as suggested previously, and that distinct presynaptic afferents that target specific sites on the dendritic tree may perform unique sets of computations.

Thin dendrites of cerebellar interneurons confer sublinear synaptic integration and a gradient of short-term plasticity

Interneurons are critical for neuronal circuit function, but how their dendritic morphologies and membrane properties influence information flow within neuronal circuits is largely unknown. We studied the spatiotemporal profile of synaptic integration and short-term plasticity in dendrites of mature cerebellar stellate cells by combining two-photon guided electrical stimulation, glutamate uncaging, electron microscopy, and modeling. Synaptic activation within thin (0.4 μm) dendrites produced somatic responses that became smaller and slower with increasing distance from the soma, sublinear subthreshold input-output relationships, and a somatodendritic gradient of short-term plasticity. Unlike most studies showing that neurons employ active dendritic mechanisms, we found that passive cable properties of thin dendrites determine the sublinear integration and plasticity gradient, which both result from large dendritic depolarizations that reduce synaptic driving force. These integrative properties allow stellate cells to act as spatiotemporal filters of synaptic input patterns, thereby biasing their output in favor of sparse presynaptic activity.

Why the brain knows more than we do: non-conscious representations and their role in the construction of conscious experience

Scientific studies have shown that non-conscious stimuli and representations influence information processing during conscious experience. In the light of such evidence, questions about potential functional links between non-conscious brain representations and conscious experience arise. This article discusses neural model capable of explaining how statistical learning mechanisms in dedicated resonant circuits could generate specific temporal activity traces of non-conscious representations in the brain. How reentrant signaling, top-down matching, and statistical coincidence of such activity traces may lead to the progressive consolidation of temporal patterns that constitute the neural signatures of conscious experience in networks extending across large distances beyond functionally specialized brain regions is then explained.

Unique somato-dendritic distribution pattern of Kv4.2 channels on hippocampal CA1 pyramidal cells

A-type K⁺ current (I_A) plays a critical role in controlling the excitability of pyramidal cell (PC) dendrites. In vitro dendritic patch-pipette recordings have demonstrated a prominent, sixfold increase in I_A density along the main apical dendrites of rat hippocampal CA1 PCs. In these cells, I_A is mediated by Kv4.2 subunits, whose precise subcellular distribution and densities in small-diameter oblique dendrites and dendritic spines are still unknown. Here we examined the densities of the Kv4.2 subunit in 13 axo-somato-dendritic compartments of CA1 PCs using a highly sensitive, high-resolution quantitative immunogold localization method (sodium dodecyl sulphate-digested freeze-fracture replica-labelling). Only an approximately 70% increase in Kv4.2 immunogold density was observed along the proximo-distal axis of main apical dendrites in the stratum radiatum with a slight decrease in density in stratum lacunosum-moleculare. A similar pattern was detected for all dendritic compartments, including main apical dendrites, small-diameter oblique dendrites and dendritic spines. The specificity of the somato-dendritic labelling was confirmed in Kv4.2^−/− tissue. No specific immunolabelling for the Kv4.2 subunit was found in SNAP-25-containing presynaptic axons. Our results demonstrate a novel distribution pattern of a voltage-gated ion channel along the somato-dendritic surface of CA1 PCs, and suggest that the increase in the I_A along the proximo-distal axis of PC dendrites cannot be solely explained by a corresponding increase in Kv4.2 channel number.

Asymmetric temporal integration of layer 4 and layer 2/3 inputs in visual cortex

Neocortical neurons in vivo receive concurrent synaptic inputs from multiple sources, including feedforward, horizontal, and feedback pathways. Layer 2/3 of the visual cortex receives feedforward input from layer 4 and horizontal input from layer 2/3. Firing of the pyramidal neurons, which carries the output to higher cortical areas, depends critically on the interaction of these pathways. Here we examined synaptic integration of inputs from layer 4 and layer 2/3 in rat visual cortical slices. We found that the integration is sublinear and temporally asymmetric, with larger responses if layer 2/3 input preceded layer 4 input. The sublinearity depended on inhibition, and the asymmetry was largely attributable to the difference between the two inhibitory inputs. Interestingly, the asymmetric integration was specific to pyramidal neurons, and it strongly affected their spiking output. Thus via cortical inhibition, the temporal order of activation of layer 2/3 and layer 4 pathways can exert powerful control of cortical output during visual processing.

Dynamic spike thresholds during synaptic integration preserve and enhance temporal response properties in the avian cochlear nucleus

Neurons of the cochlear nuclei are anatomically and physiologically specialized to optimally encode temporal and spectral information about sound stimuli, in part for binaural auditory processing. The avian cochlear nucleus magnocellularis (NM) integrates excitatory eighth nerve inputs and depolarizing GABAergic inhibition such that temporal fidelity is enhanced across the synapse. The biophysical mechanisms of this depolarizing inhibition, and its role in temporal processing, are not fully understood. We used whole-cell electrophysiology and computational modeling to examine how subthreshold excitatory inputs are integrated and how depolarizing IPSPs affect spike thresholds and synaptic integration by chick NM neurons. We found that both depolarizing inhibition and subthreshold excitatory inputs cause voltage threshold accommodation, nonlinear temporal summation, and shunting. Inhibition caused such large changes in threshold that subthreshold excitatory inputs were followed by a refractory period. We hypothesize that these large shifts in threshold eliminate spikes to asynchronous inputs, providing a mechanism for the enhanced temporal fidelity seen across the eighth nerve/cochlear nucleus synapse. Thus, depolarizing inhibition and threshold shifting hone the temporal response properties of this system so as to enhance the temporal fidelity that is essential for auditory perception.

Role of A-type potassium currents in excitability, network synchronicity, and epilepsy

A range of ionic currents have been suggested to be involved in distinct aspects of epileptogenesis. Based on pharmacological and genetic studies, potassium currents have been implicated, in particular the transient A-type potassium current (K(A)). Epileptogenic activity comprises a rich repertoire of characteristics, one of which is synchronized activity of principal cells as revealed by occurrences of for instance fast ripples. Synchronized activity of this kind is particularly efficient in driving target cells into spiking. In the recipient cell, this synchronized input generates large brief compound excitatory postsynaptic potentials (EPSPs). The fast activation and inactivation of K(A) lead us to hypothesize a potential role in suppression of such EPSPs. In this work, using computational modeling, we have studied the activation of K(A) by synaptic inputs of different levels of synchronicity. We find that K(A) participates particularly in suppressing inputs of high synchronicity. We also show that the selective suppression stems from the current's ability to become activated by potentials with high slopes. We further show that K(A) suppresses input mimicking the activity of a fast ripple. Finally, we show that the degree of selectivity of K(A) can be modified by changes to its kinetic parameters, changes of the type that are produced by the modulatory action of KChIPs and DPPs. We suggest that the wealth of modulators affecting K(A) might be explained by a need to control cellular excitability in general and suppression of responses to synchronicity in particular. Wealso suggest that compounds changing K(A)-kinetics may be used to pharmacologically improve epileptic status.

Properties of piriform cortex pyramidal cell dendrites: implications for olfactory circuit design

Unlike the neocortex, sensory input to the piriform cortex is anatomically segregated in layer 1, making it ideal for studying the dendritic integration of synaptic inputs pivotal for sensory information processing. Here we investigated dendritic integration of olfactory bulb inputs in pyramidal cells using dual patch-clamp recordings along the soma-apical dendritic axis. We found that these dendrites are relatively compact with 50% maximal somatic current loss for synaptic inputs arriving at distal dendritic regions. Distal dendrites could generate small and fast local spikes, but they had little impact on the soma, indicating that they are only weakly active. In contrast to the neocortex, we found no evidence for dendritic Ca(2+) or NMDA spikes though these dendrites actively supported action potential backpropagation with concomitant entry of Ca(2+) ions. Based on experiments and simulations we suggest that regardless of dendritic location, olfactory bulb inputs have nearly uniform potency and are distributed diffusely over the distal apical tree (layer Ia), thereby minimizing sublinear summation effects. This indicates that any stimulus feature extraction performed by these cells will occur at the soma and is based on the nearly linear sum of olfactory bulb inputs, rather than on explicitly designed clusters of functionally related synapses in the dendritic tree.

Stimulus-selective spiking is driven by the relative timing of synchronous excitation and disinhibition in cat striate neurons in vivo

What patterns of synaptic input cause cortical neurons to fire action potentials? Are they stochastic in nature, or do action potentials arise from the specific timing of synaptic input? We addressed these questions by measuring the membrane potential fluctuations associated with the generation of visually evoked action potentials in cat striate cortical neurons in vivo. In response to visual stimulation, action potentials occurred at the crest of large-amplitude, transient depolarizations (TDs) riding on sustained depolarization of the membrane potential. The magnitude, duration and rate of depolarization of these transient events were tuned for stimulus orientation. Using numerical simulations, we find that these transient events can arise from the temporal interplay between synchronous excitation and inhibition. To validate these findings, we made conductance measurements, at the preferred stimulus orientation, and showed that the TDs arise either from an increase in excitatory conductance, or from a combination of increased excitatory and decreased inhibitory conductance, both riding on sustained changes in synaptic conductances. The properties of the TDs and their underlying conductance suggest that they arise from a specific temporal interplay between synchronous excitatory and inhibitory synaptic inputs. Our results illustrate a mechanism by which the timing of synaptic inputs determines much of the spiking activity in striate cortical neurons.

Recoding patterns of sensory input: higher-order features and the function of nonlinear dendritic trees

Here analytical and simulation results are presented characterizing the recoding arising when overlapping patterns of sensor input impinge on an array of model neurons with branched thresholded dendritic trees. Thus, the neural units employed are intended to capture the integrative behavior of pyramidal cells that sustain isolated Na(+) or NMDA spikes in their branches. Given a defined set of sensor vectors, equations were derived for the probability of firing of both branches and neurons and for the expected overlap between the neural firing patterns triggered by two afferent patterns of given overlap. Thus, both the sparseness of the neural representation and the orthogonalization of overlapping vectors were computed. Simulations were then performed with an array of 1000 neurons comprising 30,000 branches to verify the analytical results and confirm their applicability to systems (which include any practicable artificial system) in which the combinatorically possible branches and neurons are severely subsampled. A means of readout and a measure of discrimination performance were provided so that the accuracy of discrimination among overlapping sensor vectors could be optimized as a function of neuron structure parameters. Good performance required both orthogonalization of the afferent patterns, so that discrimination was accurate and free of interference, and maintenance of a minimum level of neural activity, so that some neurons fired in response to each sensor pattern. It is shown that the discrimination performance achieved by arrays of neurons with branched dendritic trees could not be reached with single-compartment units, regardless of how many of the latter are used. The analytical results furnish a benchmark against which to measure further enhancements in the performance of subsequent simulated systems incorporating local neural mechanisms which, while often less amenable to closed-form analysis, are ubiquitous in biological neural circuitry.

Photolysis of caged neurotransmitters: theory and procedures for light delivery

Photolysis of "caged" compounds is a technique for releasing biologically active compounds in which the timing, rate, and spatial profile of release are controlled by light. Issues relating to the delivery of light for single-photon photolysis are presented. Specific discussions include the theories relating to how light interacts with biological tissue to produce scattering and phototoxicity, as well as the issues involved in choosing the appropriate light source. Several approaches and optical designs are presented for delivering the output of a laser to a microscopic specimen. The criteria for choosing an approach are presented. The commercial sources for the parts needed to build a photolysis system are also provided. This unit will be particularly useful for investigators interested in single-photon photolysis of caged neurotransmitters in brain slices.

Coincidence detection of convergent perforant path and mossy fibre inputs by CA3 interneurons

We performed whole-cell recordings from CA3 s. radiatum (R) and s. lacunosum-moleculare (L-M) interneurons in hippocampal slices to examine the temporal aspects of summation of converging perforant path (PP) and mossy fibre (MF) inputs. PP EPSPs were evoked from the s. lacunosum-moleculare in area CA1. MF EPSPs were evoked from the medial extent of the suprapyramidal blade of the dentate gyrus. Summation was strongly supralinear when examining PP EPSP with MF EPSP in a heterosynaptic pair at the 10 ms ISI, and linear to sublinear at longer ISIs. This pattern of nonlinearities suggests that R and L-M interneurons act as coincidence detectors for input from PP and MF. Summation at all ISIs was linear in voltage clamp mode demonstrating that nonlinearities were generated by postsynaptic voltage-dependent conductances. Supralinearity was not detected when the first EPSP in the pair was replaced by a simulated EPSP injected into the soma, suggesting that the conductances underlying the EPSP boosting were located in distal dendrites. Supralinearity was selectively eliminated with either Ni2+ (30 microm), mibefradil (10 microm) or nimodipine (15 microm), but was unaffected by QX-314. This pharmacological profile indicates that supralinearity is due to recruitment of dendritic T-type Ca2+channels by the first subthreshold EPSP in the pair. Results with the hyperpolarization-activated (Ih) channel blocker ZD 7288 (50 microm) revealed that Ih restricted the time course of supralinearity for coincidently summed EPSPs, and promoted linear to sublinear summation for asynchronous EPSPs. We conclude that coincidence detection results from the counterbalanced activation of T-type Ca2+ channels and inactivation of Ih.

Spatiotemporal analyses of interactions between entorhinal and CA1 projections to the subiculum in rat brain slices

The subiculum and the entorhinal cortex (EC) are important structures in processing and transmitting information between the neocortex and the hippocampus. The subiculum potentially receives information from the EC through two routes. In addition to a direct projection from EC to the subiculum, there is an indirect polysynaptic connection. The latter uses a number of possible pathways, which all converge onto the final projection from the hippocampal field CA1 to the subiculum. In this series of experiments we investigated to what extent activity in both pathways influences population activity of subicular neurons. We used voltage sensitive dyes in combined hippocampal-EC slices of the rat to measure the spatio-temporal activity patterns. To activate the two inputs to the subiculum, stimulation electrodes were placed in the stratum oriens/alveus of CA1 and in layer III of the medial EC. The response patterns evoked in the subiculum after electrical stimulation of each of these input pathways separately were compared with the response patterns after simultaneous stimulation of both areas (medial EC + CA1). A comparison of the computed added responses of the two individual stimulations with the measured responses after simultaneous stimulation suggests that both inputs are linearly added in the subiculum with very little nonlinear interactions. This strongly suggests that in the subiculum interaction at a single cell level of the direct and the indirect pathways from the EC is an unlikely scenario.

Timing and location of synaptic inputs determine modes of subthreshold integration in striatal medium spiny neurons

Medium spiny neurons (MSNs) are the principal cells of the striatum and perform a central role in sensorimotor processing. MSNs must integrate many excitatory inputs located across their dendrites to fire action potentials and enable striatal function. However, the dependence of synaptic responses on the temporal and spatial distribution of these inputs remains unknown. Here, we use whole-cell recordings, two-photon microscopy, and two-photon glutamate uncaging to examine subthreshold synaptic integration in MSNs from acute rat brain slices. We find that synaptic responses can summate sublinearly, linearly, or supralinearly depending on the spatiotemporal pattern of activity. Repetitive activity at single inputs leads to sublinear summation, reflecting long-lived AMPA receptor desensitization. In contrast, asynchronous activity at multiple inputs generates linear summation, with synapses on neighboring spines functioning independently. Finally, synchronous activity at multiple inputs triggers supralinear summation at depolarized potentials, reflecting activation of NMDA receptors and L-type calcium channels. Thus, the properties of subthreshold integration in MSNs are determined by the distribution of synaptic inputs and the differential activation of multiple postsynaptic conductances.

Temporal patterning of saccadic eye movement signals

Electrical microstimulation is used widely in experimental neurophysiology to examine causal links between specific brain areas and their behavioral functions and is used clinically to treat neurological and psychiatric disorders in patients. Typically, microstimulation is applied to local brain regions as a train of equally spaced current pulses. We were interested in the sensitivity of a neural circuit to a train of variably spaced pulses, as is observed in physiological spike trains. We compared the effect of fixed, decelerating, accelerating, and randomly varying microstimulation patterns on the likelihood and metrics of eye movements evoked from the frontal eye field of monkeys, while holding the mean interpulse interval constant. Our results demonstrate that the pattern of microstimulation pulses strongly influences the probability of evoking a saccade, as well as the metrics of the saccades themselves. Specifically, the pattern most closely resembling physiological spike trains (accelerating pattern) was most effective at evoking a saccade, three times more so than the least effective decelerating pattern. A saccade-triggered average of effective random trains confirmed the positive relationship between accelerating rate and efficacy. These results have important implications for the use of electrical microstimulation in both experimental and clinical settings and suggest a means to study the role of temporal pattern in the encoding of behavioral and cognitive functions.

Spike timing and reliability in cortical pyramidal neurons: effects of EPSC kinetics, input synchronization and background noise on spike timing

In vivo studies have shown that neurons in the neocortex can generate action potentials at high temporal precision. The mechanisms controlling timing and reliability of action potential generation in neocortical neurons, however, are still poorly understood. Here we investigated the temporal precision and reliability of spike firing in cortical layer V pyramidal cells at near-threshold membrane potentials. Timing and reliability of spike responses were a function of EPSC kinetics, temporal jitter of population excitatory inputs, and of background synaptic noise. We used somatic current injection to mimic population synaptic input events and measured spike probability and spike time precision (STP), the latter defined as the time window (Δt) holding 80% of response spikes. EPSC rise and decay times were varied over the known physiological spectrum. At spike threshold level, EPSC decay time had a stronger influence on STP than rise time. Generally, STP was highest (≤2.45 ms) in response to synchronous compounds of EPSCs with fast rise and decay kinetics. Compounds with slow EPSC kinetics (decay time constants>6 ms) triggered spikes at lower temporal precision (≥6.58 ms). We found an overall linear relationship between STP and spike delay. The difference in STP between fast and slow compound EPSCs could be reduced by incrementing the amplitude of slow compound EPSCs. The introduction of a temporal jitter to compound EPSCs had a comparatively small effect on STP, with a tenfold increase in jitter resulting in only a five fold decrease in STP. In the presence of simulated synaptic background activity, precisely timed spikes could still be induced by fast EPSCs, but not by slow EPSCs.

Novel approach to real-time flash photolysis and confocal [Ca2+] imaging

Flash photolysis of "caged" compounds using ultraviolet light is a powerful experimental technique for producing rapid changes in concentrations of bioactive signaling molecules. Studies that employ this technique have used diverse strategies for controlling the spatial and temporal application of light to the specimen. In this paper, we describe a new system for flash photolysis that delivers light from a pulsed, adjustable intensity laser through an optical fiber coupled into the epifluorescence port of a commercial confocal microscope. Photolysis is achieved with extremely brief (5 ns) pulses of ultraviolet light (355 nm) that can be synchronized with respect to confocal laser scanning. The system described also localizes the UV intensity spatially so that uncaging only occurs in defined subcellular regions; moreover, because the microscope optics are used in localization, the photolysis volume can be easily adjusted. Experiments performed on rat ventricular myocytes loaded with the Ca(2+) indicator fluo-3 and the Ca(2+) cage o-nitrophenyl ethylene glycol bis(2-aminoethyl ether)-N,N,N'N'-tetraacetic acid (NP-EGTA) demonstrate the system's capabilities. Localized intracellular increases in [Ca(2+)] can trigger sarcoplasmic reticular Ca(2+) release events such as Ca(2+) sparks and, under certain conditions, regenerative Ca(2+) waves. This relatively simple and inexpensive system is, therefore, a useful tool for examining local signaling in the heart and other tissues.

Stimulus selectivity is enhanced by voltage-dependent conductances in combination-sensitive neurons

Central sensory neurons often respond selectively to particular combinations of stimulus attributes, but we know little about the underlying cellular mechanisms. The weakly electric fish Gymnarchus discriminates the sign of the frequency difference (Df) between a neighbor's electric organ discharge (EOD) and its own EOD by comparing temporal patterns of amplitude modulation (AM) and phase modulation (PM). Sign-selective neurons in the midbrain respond preferentially to either positive frequency differences (Df >0 selective) or negative frequency differences (Df <0 selective). To study the mechanisms of combination sensitivity, we made whole cell intracellular recordings from sign-selective midbrain neurons in vivo and recorded postsynaptic potential (PSP) responses to AM, PM, Df >0, and Df <0. Responses to AM and PM consisted of alternating excitatory and inhibitory PSPs. These alternating responses were in phase for the preferred sign of Df and offset for the nonpreferred sign of Df. Therefore a certain degree of sign selectivity was predicted by a linear sum of the responses to AM and PM. Responses to the nonpreferred sign of Df, but not the preferred sign of Df, were substantially weaker than linear predictions, causing a significant increase in the actual degree of sign selectivity. By using various levels of current clamp and comparing our results to simple models of synaptic integration, we demonstrate that this decreased response to the nonpreferred sign of Df is caused by a reduction in voltage-dependent excitatory conductances. This finding reveals that nonlinear decoders, in the form of voltage-dependent conductances, can enhance the selectivity of single neurons for particular combinations of stimulus attributes.

Systems-level modeling of neuronal circuits for leech swimming

This paper describes a mathematical model of the neuronal central pattern generator (CPG) that controls the rhythmic body motion of the swimming leech. The systems approach is employed to capture the neuronal dynamics essential for generating coordinated oscillations of cell membrane potentials by a simple CPG architecture with a minimal number of parameters. Based on input/output data from physiological experiments, dynamical components (neurons and synaptic interactions) are first modeled individually and then integrated into a chain of nonlinear oscillators to form a CPG. We show through numerical simulations that the values of a few parameters can be estimated within physiologically reasonable ranges to achieve good fit of the data with respect to the phase, amplitude, and period. This parameter estimation leads to predictions regarding the synaptic coupling strength and intrinsic period gradient along the nerve cord, the latter of which agrees qualitatively with experimental observations.

Early visuomotor representations revealed from evoked local field potentials in motor and premotor cortical areas

Local field potentials (LFPs) recorded from primary motor cortex (MI) have been shown to be tuned to the direction of visually guided reaching movements, but MI LFPs have not been shown to be tuned to the direction of an upcoming movement during the delay period that precedes movement in an instructed-delay reaching task. Also, LFPs in dorsal premotor cortex (PMd) have not been investigated in this context. We therefore recorded LFPs from MI and PMd of monkeys (Macaca mulatta) and investigated whether these LFPs were tuned to the direction of the upcoming movement during the delay period. In three frequency bands we identified LFP activity that was phase-locked to the onset of the instruction stimulus that specified the direction of the upcoming reach. The amplitude of this activity was often tuned to target direction with tuning widths that varied across different electrodes and frequency bands. Single-trial decoding of LFPs demonstrated that prediction of target direction from this activity was possible well before the actual movement is initiated. Decoding performance was significantly better in the slowest-frequency band compared with that in the other two higher-frequency bands. Although these results demonstrate that task-related information is available in the local field potentials, correlations among these signals recorded from a densely packed array of electrodes suggests that adequate decoding performance for neural prosthesis applications may be limited as the number of simultaneous electrode recordings is increased.

State-dependent dendritic computation in hippocampal CA1 pyramidal neurons

Depending on the behavioral state, hippocampal CA1 pyramidal neurons receive very distinct patterns of synaptic input and likewise produce very different output patterns. We have used simultaneous dendritic and somatic recordings and multisite glutamate uncaging to investigate the relationship between synaptic input pattern, the form of dendritic integration, and action potential output in CA1 neurons. We found that when synaptic input arrives asynchronously or highly distributed in space, the dendritic arbor performs a linear integration that allows the action potential rate and timing to vary as a function of the quantity of the input. In contrast, when synaptic input arrives synchronously and spatially clustered, the dendritic compartment receiving the clustered input produces a highly nonlinear integration that leads to an action potential output that is extraordinarily precise and invariant. We also present evidence that both of these forms of information processing may be independently engaged during the two distinct behavioral states of the hippocampus such that individual CA1 pyramidal neurons could perform two different state-dependent computations: input strength encoding during theta states and feature detection during sharp waves.

Role of hyperpolarization-activated conductances in the lateral superior olive: a modeling study

This modeling study examines the possible functional roles of two hyperpolarization-activated conductances in lateral superior olive (LSO) principal neurons. Inputs of these LSO neurons are transformed into an output, which provides a firing-rate code for a certain interaural sound intensity difference (IID) range. Recent experimental studies have found pharmacological evidence for the presence of both the Gh conductance as well as the inwardly rectifying outward GKIR conductance in the LSO. We addressed the question of how these conductances influence the dynamic range (IID versus firing rate). We used computer simulations of both a point-neuron model and a two-compartmental model to investigate this issue, and to determine the role of these conductances in setting the dynamic range of these neurons. The width of the dynamic regime, the frequency-current (f-I) function, first-spike latency, subthreshold oscillations and the interplay between the two hyperpolarization activated conductances are discussed in detail. The in vivo non-monotonic IID-firing rate function in a subpopulation of LSO neurons is in good correspondence with our simulation predictions. Two compartmental model simulation results suggest segregation of Gh and GKIR conductances on different compartments, as this spatial configuration could explain certain experimental results.

Effects of noise correlations on information encoding and decoding

Response variability is often correlated across populations of neurons, and these noise correlations may play a role in information coding. In previous studies, this possibility has been examined from the encoding and decoding perspectives. Here we used d prime and related information measures to examine how studies of noise correlations from these two perspectives are related. We found that for a pair of neurons, the effect of noise correlations on information decoding can be zero when the effect of noise correlations on the information encoded obtains its largest positive or negative values. Furthermore, there can be no effect of noise correlations on the information encoded when it has an effect on information decoding. We also measured the effect of noise correlations on information encoding and decoding in simultaneously recorded neurons in the supplementary motor area to see how well d prime accounted for the information actually present in the neural responses and to see how noise correlations affected encoding and decoding in real data. These analyses showed that d prime provides an accurate measure of information encoding and decoding in our population of neurons. We also found that the effect of noise correlations on information encoding was somewhat larger than the effect of noise correlations on information decoding, but both were relatively small. Finally, as predicted theoretically, the effects of correlations were slightly greater for larger ensembles (3-8 neurons) than for pairs of neurons.

On the use of superadditivity as a metric for characterizing multisensory integration in functional neuroimaging studies

A growing number of brain imaging studies are being undertaken in order to better understand the contributions of multisensory processes to human behavior and perception. Many of these studies are designed on the basis of the physiological findings from single neurons in animal models, which have shown that multisensory neurons have the capacity for integrating their different sensory inputs and give rise to a product that differs significantly from either of the unisensory responses. At certain points these multisensory interactions can be superadditive, resulting in a neural response that exceeds the sum of the unisensory responses. Because of the difficulties inherent in interpreting the results of imaging large neuronal populations, superadditivity has been put forth as a stringent criterion for identifying potential sites of multisensory integration. In the present manuscript we discuss issues related to using the superadditive model in human brain imaging studies, focusing on population responses to multisensory stimuli and the relationship between single neuron measures and functional brain imaging measures. We suggest that the results of brain imaging studies be interpreted with caution in regards to multisensory integration. Future directions for imaging multisensory integration are discussed in light of the ideas presented.

Dynamic spatiotemporal synaptic integration in cortical neurons: neuronal gain, revisited

Gain modulation is a ubiquitous phenomenon in cortical neurons, providing flexibility to operate under changing conditions. The prevailing view is that this modulation reflects a change in the relationship between mean input and output firing rate brought about by variation in neuronal membrane characteristics. An alternative mechanism is proposed for neuronal gain modulation that takes into account the capability of cortical neurons to process spatiotemporal synaptic correlations. Through the use of numerical simulations, it is shown that voltage-gated and leak conductances, membrane potential, noise, and input firing rate modify the sensitivity of cortical neurons to the degree of temporal correlation between their synaptic inputs. These changes are expressed in a change of the temporal window for synaptic integration and the range of input correlation over which response probability is graded. The study also demonstrates that temporal integration depends on the distance between the inputs and that this interplay of space and time is modulated by voltage-gated and leak conductances. Thus, gain modulation may reflect a change in the relationship between spatiotemporal synaptic correlations and output firing probability. It is further proposed that by acting synergistically with the network, dynamic spatiotemporal synaptic integration in cortical neurons may serve a functional role in the formation of dynamic cell assemblies.

Controlling synaptic input patterns in vitro by dynamic photo stimulation

Recent experimental and theoretical work indicates that both the intensity and the temporal structure of synaptic activity strongly modulate the integrative properties of single neurons in the intact brain. However, studying these effects experimentally is complicated by the fact that, in experimental systems, network activity is either absent, as in the acute slice preparation, or difficult to monitor and to control, as in in vivo recordings. Here, we present a new implementation of neurotransmitter uncaging in acute brain slices that uses functional projections to generate tightly controlled, spatio-temporally structured synaptic input patterns in individual neurons. For that, a set of presynaptic neurons is activated in a precisely timed sequence through focal photolytic release of caged glutamate with the help of a fast laser scanning system. Integration of synaptic inputs can be studied in postsynaptic neurons that are not directly stimulated with the laser, but receive input from the targeted neurons through intact axonal projections. Our new approach of dynamic photo stimulation employs functional synapses, accounts for their spatial distribution on the dendrites, and thus allows study of the integrative properties of single neurons with physiologically realistic input. Data obtained with our new technique suggest that, not only the neuronal spike generator, but also synaptic transmission and dendritic integration in neocortical pyramidal cells, can be highly reliable.

Intrinsic noise in cultured hippocampal neurons: experiment and modeling

Ion channels open and close stochastically. The fluctuation of these channels represents an intrinsic source of noise that affects the input-output properties of the neuron. We combined whole-cell measurements with biophysical modeling to characterize the intrinsic stochastic and electrical properties of single neurons as observed at the soma. We measured current and voltage noise in 18 d postembryonic cultured neurons from the rat hippocampus, at various subthreshold and near-threshold holding potentials in the presence of synaptic blockers. The observed current noise increased with depolarization, as ion channels were activated, and its spectrum demonstrated generalized 1/f behavior. Exposure to TTX removed a significant contribution from Na+ channels to the noise spectrum, particularly at depolarized potentials, and the resulting spectrum was now dominated by a single Lorentzian (1/f2) component. By replacing the intracellular K+ with Cs+, we demonstrated that a major portion of the observed noise was attributable to K+ channels. We compared the measured power spectral densities to a 1-D cable model of channel fluctuations based on Markov kinetics. We found that a somatic compartment, in combination with a single equivalent cylinder, described the effective geometry from the viewpoint of the soma. Four distinct channel populations were distributed in the membrane and modeled as Lorentzian current noise sources. Using the NEURON simulation program, we summed up the contributions from the spatially distributed current noise sources and calculated the total voltage and current noise. Our quantitative model reproduces important voltage- and frequency-dependent features of the data, accounting for the 1/f behavior, as well as the effects of various blockers.

Intrinsic and circuit properties favor coincidence detection for decoding oscillatory input

In the insect olfactory system the antennal lobe generates oscillatory synchronization of its output as a framework for coincidence detection by its target, the mushroom body (MB). The intrinsic neurons of the MB (Kenyon cells, KCs) are thus a good model system in which to investigate the functional relevance of oscillations and neural synchronization. We combine electrophysiological and modeling approaches to examine how intrinsic and circuit properties might contribute to the preference of KCs for coincident input and how their decoding of olfactory information is affected by the absence of oscillatory synchronization in their input. We show that voltage-dependent subthreshold properties of KCs bring about a supralinear summation of their inputs, favoring responses to coincident EPSPs. Abolishing oscillatory synchronization weakens the preference of KCs for coincident input and causes a large reduction in their odor specificity. Finally, we find that a decoding strategy that is based on coincidence detection enhances both noise tolerance and input discriminability by KCs.

Integration of synaptic responses to neighboring whiskers in rat barrel cortex in vivo

Characterizing input integration at the single-cell level is a critical step to understanding cortical function, particularly when sensory stimuli are represented over wide cortical areas and single cells exhibit large receptive fields. To study synaptic integration of sensory inputs, we made intracellular recordings from the barrel cortex of anesthetized rats in vivo. For each cell, we deflected the principal whisker (PW) either alone or preceded by the deflection of a single adjacent whisker (AW) at an interval of 20 or 3 ms. At the 20-ms interval in all cases, prior AW deflection significantly suppressed the PW-evoked spike output and caused the underlying synaptic response to reach a peak Vm less depolarized than that arising from PW deflection alone. The decrease in peak Vm was not attributed to hyperpolarizing inhibition but to a divisive reduction in PW-evoked PSP amplitude. The reduction in amplitude was not a result of shunting inhibition but was mostly a result of removal of the synaptic drive, or disfacilitation. When the AW-PW interval was shortened to 3 ms, spike suppression was observed in a subset of the cells studied. In most cases, a divisive reduction in synaptic response amplitude was offset by summation with the preceding AW-evoked depolarization. To determine whether suppression is a general feature of synaptic integration by barrel cortex neurons, we also characterized the interaction of responses evoked by local electrical stimulation. In contrast to the whisker data, we found that responses to paired stimulation at the same intervals produced more spikes and reached a peak Vm more depolarized than the individual responses alone, suggesting that whisker-evoked suppression is not a result of postsynaptic mechanisms. Instead, we propose that cross-whisker response suppression depends on sensory-specific mechanisms at cortical and subcortical levels.

Functional Topography of Converging Visual and Auditory Inputs to Neurons in the Rat Superior Colliculus

We have used a slice preparation of the infant rat midbrain to examine converging inputs onto neurons in the deeper multisensory layers of the superior colliculus (dSC). Electrical stimulation of the superficial visual layers (sSC) and of the auditory nucleus of the brachium of the inferior colliculus (nBIC) evoked robust monosynaptic responses in dSC cells. Furthermore, the inputs from the sSC were found to be topographically organized as early as the second postnatal week and thus before opening of the eyes and ear canals. This precocious topography was found to be sculpted by GABAA-mediated inhibition of a more widespread set of connections. Tracer injections in the nBIC, both in coronal slices as well as in hemisected brains, confirmed a robust projection originating in the nBIC with distinct terminals in the proximity of the cell bodies of dSC neurons. Combined stimulation of the sSC and nBIC sites revealed that the presumptive visual and auditory inputs are summed linearly. Finally, whereas either input on its own could manifest a significant degree of paired-pulse facilitation, temporally offset stimulation of the two sites revealed no synaptic interactions, indicating again that the two inputs function independently. Taken together, these data provide the first detailed intracellular analysis of convergent sensory inputs onto dSC neurons and form the basis for further exploration of multisensory integration and developmental plasticity.

Contribution of Ih and GABAB to Synaptically Induced Afterhyperpolarizations in CA1: A Brake on the NMDA Response

CA1 pyramidal cells receive two major excitatory inputs: the perforant path (PP) terminates in the most distal dendrites, whereas the Schaffer collaterals (SC) terminate more proximally. We have examined the mechanism of the afterhyperpolarization (AHP) that follows single subthreshold excitatory postsynaptic potentials (EPSPs) in these inputs. The AHPs were not reduced by a GABAA antagonist or by agents that block Ca2+ entry. Application of the Ih blocker, ZD7288, partially blocked the AHP in the PP; the substantial remaining component was blocked by 2-hydroxysaclofen, a GABAB antagonist. In contrast, the AHP in the SC depends nearly completely on Ih, with almost no GABAB component. Thus postsynaptic GABAB receptors appear to be preferentially involved at distal synapses, consistent with the spatial distribution of GABAB receptors and g protein-coupled inward rectifying potassium (GIRK) channels. GABAB does, however, play a role at proximal synapses through presynaptic suppression of glutamate release, a mechanism that is much weaker at distal synapses. Experiments were conducted to explore the functional role of the AHP in the PP, which has a higher N-methyl-d-aspartate (NMDA)/AMPA ratio than the SC. Blockade of the AHP converted a response that had a small NMDA component to one that had a large component. These results indicate that the Ih and postsynaptic GABAB conductances act as a brake on distally generated NMDA responses.

Coding and transmission of information by neural ensembles

The brain processes information about sensory stimuli and motor intentions using a massive ensemble of neurons arrayed in parallel. Individual neurons receive convergent inputs from thousands of other neurons, leading to the possibility that patterns of spikes across the input neurons might be crucial components of the neural code. Recently, advances in multielectrode recording techniques have allowed several laboratories to investigate the nature of the interactions between neurons, and their potential role in information coding. Several recent studies have found that the amount of information coded by correlated activity about sensory and motor variables is small, casting doubt on the hypothesis that correlations between pairs of neurons are important for information coding. However, other studies have documented the appearance of coherent oscillations, during particular task epochs and conditions that require selective processing of sensory information, supporting the hypothesis that coherent oscillations between neurons might reflect the dynamic flow of information in the brain.

Computational subunits in thin dendrites of pyramidal cells

The thin basal and oblique dendrites of cortical pyramidal neurons receive most of the synaptic inputs from other cells, but their integrative properties remain uncertain. Previous studies have most often reported global linear or sublinear summation. An alternative view, supported by biophysical modeling studies, holds that thin dendrites provide a layer of independent computational 'subunits' that sigmoidally modulate their inputs prior to global summation. To distinguish these possibilities, we combined confocal imaging and dual-site focal synaptic stimulation of identified thin dendrites in rat neocortical pyramidal neurons. We found that nearby inputs on the same branch summed sigmoidally, whereas widely separated inputs or inputs to different branches summed linearly. This strong spatial compartmentalization effect is incompatible with a global summation rule and provides the first experimental support for a two-layer 'neural network' model of pyramidal neuron thin-branch integration. Our findings could have important implications for the computing and memory-related functions of cortical tissue.

Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell

The rules of synaptic integration in pyramidal cells remain obscure, in part due to conflicting interpretations of existing experimental data. To clarify issues, we developed a CA1 pyramidal cell model calibrated with a broad spectrum of in vitro data. Using simultaneous dendritic and somatic recordings and combining results for two different response measures (peak versus mean EPSP), two different stimulus formats (single shock versus 50 Hz trains), and two different spatial integration conditions (within versus between-branch summation), we found that the cell's subthreshold responses to paired inputs are best described as a sum of nonlinear subunit responses, where the subunits correspond to different dendritic branches. In addition to suggesting a new type of experiment and providing testable predictions, our model shows how conclusions regarding synaptic arithmetic can be influenced by an array of seemingly innocuous experimental design choices.

Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo

Several theories have proposed a functional role for response synchronization in sensory perception. Critics of these theories have argued that selective synchronization is physiologically implausible when cortical networks operate at high levels of activity. Using intracellular recordings from visual cortex in vivo, in combination with numerical simulations, we find dynamic changes in spike threshold that reduce cellular sensitivity to slow depolarizations and concurrently increase the relative sensitivity to rapid depolarizations. Consistent with this, we find that spike activity and high-frequency fluctuations in membrane potential are closely correlated and that both are more tightly tuned for stimulus orientation than the mean membrane potential. These findings suggest that under high-input conditions the spike-generating mechanism adaptively enhances the sensitivity to synchronous inputs while simultaneously decreasing the sensitivity to temporally uncorrelated inputs.

Optical monitoring of synaptic summation along the dendrites of CA1 pyramidal neurons

The primary function of neurons is to integrate synaptic inputs and to transmit the results to other cells. Recent studies with somatic whole-cell recordings have shown that separate excitatory inputs to hippocampal or cortical pyramidal neurons are summated non-linearly. In the present study, we examined how postsynaptic potentials (PSPs) are summated along the dendrites employing fast optical voltage imaging techniques. Rat hippocampal slices were stained with a fluorescent voltage-sensitive dye (JPW1114) and optical signals were monitored with a 16 x 16 photodiode array system. Two independent input pathways were stimulated individually or in pairs through glass electrodes such that different locations of the dendrites received separate synaptic inputs. We found that (1) the summation of PSPs was sub-linear along the entirety of dendrites, (2) the blockade of GABA(A) receptors suppressed sub-linearity and (3) further blockade of GABA(B) receptors suppressed sub-linearity of the summation of separate inputs on apical dendrites. Our study demonstrates that pyramidal neurons integrate PSPs linearly along the entirety of dendrites; moreover, GABAergic inputs are responsible for maintaining sub-linear summation in CA1 pyramidal neurons.

GABAergic control of synaptic summation in hippocampal CA1 pyramidal neurons

The primary function of neurons is to integrate synaptic inputs and to transmit the results to other cells. It was shown previously that separate excitatory inputs to hippocampal pyramidal neurons are summated nonlinearly. In the hippocampus, responses of pyramidal neurons are influenced by GABAergic inputs in feed-forward or feedback manner, and also by oscillatory network activities. It is likely that these GABAergic inputs regulate the way synaptic inputs are summated. To examine the roles of GABAergic inputs on synaptic summation, we made whole-cell recordings from the cell bodies of CA1 pyramidal neurons in rat hippocampal slices while stimulating two independent input pathways with short interstimulus intervals, and examined the manner by which postsynaptic potentials were summated. We found that: 1) the summation of the perforant pathway and the Schaffer collateral pathway inputs was sublinear when the interval between two inputs was shorter than 30 ms, 2) the blockade of GABA(A) receptors partially suppressed the sublinearity, and 3) further blockade of GABA(B) receptors removed the sublinearity totally. We also found that 4) the summation was superlinear under the concomitant blockade of GABA(A) and GABA(B) receptors when the two inputs arrived with no delay. Thus our study demonstrates that GABAergic inputs are responsible for keeping the summation of two separate inputs on CA1 pyramidal neurons sublinear.

Jun, Fos and Krox in the thalamus after C-fiber stimulation: coincident-input-dependent expression, expression across somatotopic boundaries, and nucleolar translocation

Expression of the inducible transcription factors Jun, Fos and Krox is commonly used to map neurons in the brain that are activated by sensory inputs. However, some neurons known to be electrically excited by such inputs do not always express these factors. In particular, stimulation of hindlimb sensory nerve C-fibers induces expression of c-Fos in the medial thalamus (the mediodorsal, intermediodorsal, centrolateral and centromedial), but not in the lateral thalamus (the ventroposterolateral, ventroposteromedial and posterior group). We hypothesized that c-Fos expression might only occur in these lateral areas after more complex stimulation patterns, or that only other transcription factors can be induced in these areas by such stimuli. Thus we examined the effects of single, repeated and coincident C-fiber inputs on expression of six inducible transcription factors in the medial, lateral and reticular thalamus of the rat. A weak C-fiber input caused by noxious mechanical stimulation of the skin of one hindpaw did not induce expression of c-Fos, FosB, Krox-20 or Krox-24; but it did reduce the basal expressions of c-Jun and JunD in both the medial and lateral areas. An intense input produced by electrical stimulation of all the C-fibers in one sciatic nerve also failed to induce expression of c-Fos, FosB, Krox-20 or Krox-24 in the medial or lateral areas. However, in the medial thalamus it increased c-Jun and reduced the basal expression of JunD, whereas in the lateral thalamus it had no effect on c-Jun but again reduced the basal expression of JunD. With repeated stimulation, i.e. when the noxious stimulus was applied to the contralateral hindpaw 6 h after the sciatic stimulation, there was again no induction of c-Fos, FosB or Krox-20 in the medial thalamus; but there was an increase in c-Jun and Krox-24, and a decrease in JunD levels. In the lateral thalamus the repeated stimulation again failed to induce c-Fos, but the expressions of FosB, c-Jun and Krox-24 were increased, and that of JunD was again reduced. With coincident stimulation, i.e. when a stimulus was applied to each hindpaw simultaneously, c-Fos and Krox-24 remained absent; but there was a marked induction of FosB and Krox-20, a strong repression of c-Jun, and no effect or a reduction of the basal levels of JunD. This coincident stimulation also caused FosB to appear in the nucleolus of many thalamic neurons. MK-801, but not L-NAME, blocked all these changes. In summary, noxious stimulation affects the expression of all transcription factors in the medial, lateral and reticular thalamus in a complex manner depending upon the inducible transcription factor considered, the thalamic nucleus, and the stimulation paradigm. The expression of some transcription factors uniquely after simultaneous inputs suggests they act as coincidence detectors at the gene level.