Dynamic Spatiotemporal Synaptic Integration in Cortical Neurons: Neuronal Gain, Revisited

2005 ◽  
Vol 94 (4) ◽  
pp. 2785-2796 ◽  
Author(s):  
Rony Azouz
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Temporal Integration ◽  
Synaptic Integration ◽  
Neuronal Membrane ◽  
Network Dynamic ◽  
Alternative Mechanism ◽  
Gain Modulation ◽  
Voltage Gated ◽  
The Relationship

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.

Possible Effects of Depolarizing GABAA Conductance on the Neuronal Input–Output Relationship: A Modeling Study

2005 ◽  
Vol 93 (6) ◽  
pp. 3504-3523 ◽  
Author(s):  
Kenji Morita ◽  
Kunichika Tsumoto ◽  
Kazuyuki Aihara
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Reversal Potential ◽  
Pyramidal Cells ◽  
Resting Potential ◽  
Input Output ◽  
Wide Range ◽  
The Relationship

Recent in vitro experiments revealed that the GABAA reversal potential is about 10 mV higher than the resting potential in mature mammalian neocortical pyramidal cells; thus GABAergic inputs could have facilitatory, rather than inhibitory, effects on action potential generation under certain conditions. However, how the relationship between excitatory input conductances and the output firing rate is modulated by such depolarizing GABAergic inputs under in vivo circumstances has not yet been understood. We examine herewith the input–output relationship in a simple conductance-based model of cortical neurons with the depolarized GABAA reversal potential, and show that a tonic depolarizing GABAergic conductance up to a certain amount does not change the relationship between a tonic glutamatergic driving conductance and the output firing rate, whereas a higher GABAergic conductance prevents spike generation. When the tonic glutamatergic and GABAergic conductances are replaced by in vivo–like highly fluctuating inputs, on the other hand, the effect of depolarizing GABAergic inputs on the input–output relationship critically depends on the degree of coincidence between glutamatergic input events and GABAergic ones. Although a wide range of depolarizing GABAergic inputs hardly changes the firing rate of a neuron driven by noncoincident glutamatergic inputs, a certain range of these inputs considerably decreases the firing rate if a large number of driving glutamatergic inputs are coincident with them. These results raise the possibility that the depolarized GABAA reversal potential is not a paradoxical mystery, but is instead a sophisticated device for discriminative firing rate modulation.

Computational Studies of Gain Modification by Serotonin in Pyramidal Neurons of Prefrontal Coxtex

2006 ◽  
Author(s):  
Guoshi Li ◽  
Harvey C. Cline ◽  
Pierre Blier ◽  
Satish Nair
Keyword(s):  
Prefrontal Cortex ◽  
Firing Rate ◽  
Cortical Neurons ◽  
Pyramidal Neurons ◽  
Input Resistance ◽  
Square Root ◽  
Gain Modulation ◽  
Cellular Mechanisms ◽  
Brain Functions ◽  
A Current

Serotonin (5-HT) is widely implicated in brain functions and diseases, but the cellular mechanisms underlying 5-HT functions in the brain are not well understood (Zhang and Arsenault, 2005). Recent experiments (Zhang and Arsenault, 2005) have shown that 5-HT substantially increased the slope (gain) of the firing rate current (F-I) curve in layer 5 pyramidal neurons of the rat prefrontal cortex and this effect was limited to the range of firing rate (0-10 Hz) that is known to behaviourally relevant. Furthermore, it was found that 5-HT mediated gain increase was due to a reduction of the afterhyperpolarization (AHP) and an induction of the slow afterdepolarization (ADP), regardless of changes in the membrane potential, the input resistance or the properties of action potentials. To investigate this frequency-dependent gain modulation of 5-HT on the prefrontal cortex neurons, conductance-based Hodgkin-Huxley type models of the regular spiking (RS) cells in the prefrontal cortex are developed using a step by step approach. We first show that a model with an A current displays a square-root form F-I curve with higher slope at low frequency. However, for the same range of current injection steps used in experiment, the frequency range goes beyond 20 Hz, suggesting the presence of other hyperpolarizing currents in the model. As suggested by the experiment (Zhang and Arsenault, 2005), AHP currents (fast AHP, medium AHP and slow AHP) are included in the model to simulate 5-HT effect. Simulations show that AHP currents effectively linearize the F-I curve and decrease the slope of F-I curve in general, thus reducing the neuronal excitability. Since the slow AHP current is a target of 5-HT, the strength of this current is reduced gradually and the F-I curves are plotted together for comparison. The results indicate that with decreasing slow AHP strength, the current thresholds for repetitive spiking decreases and the slopes of the F-I curves increase in general. A square-root form F-I curve is not evident until the slow AHP current is blocked completely. This suggests that the medium AHP current also play a role in linearizing the F-I curve besides the slow AHP current. Based on current findings, a full model with both A current and AHP currents is being constructed to match the experimental data more closely so the mechanism of 5-HT on gain modulation of prefrontal cortical neurons can be better understood.

scholarly journals Quantitative Assessment of the Distributions of Membrane Conductances Involved in Action Potential Backpropagation Along Basal Dendrites

2009 ◽  
Vol 101 (3) ◽  
pp. 1524-1541 ◽  
Author(s):  
Corey D. Acker ◽  
Srdjan D. Antic
Keyword(s):  
Cortical Neurons ◽  
Action Potentials ◽  
Synaptic Integration ◽  
Membrane Properties ◽  
Delayed Rectifier ◽  
Published Data ◽  
Membrane Excitability ◽  
Voltage Gated ◽  
Prefrontal Cortical ◽  
Basal Dendrites

Basal dendrites of prefrontal cortical neurons receive strong synaptic drive from recurrent excitatory synaptic inputs. Synaptic integration within basal dendrites is therefore likely to play an important role in cortical information processing. Both synaptic integration and synaptic plasticity depend crucially on dendritic membrane excitability and the backpropagation of action potentials. We carried out multisite voltage-sensitive dye imaging of membrane potential transients from thin basal branches of prefrontal cortical pyramidal neurons before and after application of channel blockers. We found that backpropagating action potentials (bAPs) are predominantly controlled by voltage-gated sodium and A-type potassium channels. In contrast, pharmacologically blocking the delayed rectifier potassium, voltage-gated calcium, or Ih conductance had little effect on dendritic AP propagation. Optically recorded bAP waveforms were quantified and multicompartmental modeling was used to link the observed behavior with the underlying biophysical properties. The best-fit model included a nonuniform sodium channel distribution with decreasing conductance with distance from the soma, together with a nonuniform (increasing) A-type potassium conductance. AP amplitudes decline with distance in this model, but to a lesser extent than previously thought. We used this model to explore the mechanisms underlying two sets of published data involving high-frequency trains of APs and the local generation of sodium spikelets. We also explored the conditions under which IA down-regulation would produce branch strength potentiation in the proposed model. Finally, we discuss the hypothesis that a fraction of basal branches may have different membrane properties compared with sister branches in the same dendritic tree.

Computer Simulation of the Responses of Human Motoneurons to Composite 1A EPSPS: Effects of Background Firing Rate

1997 ◽  
Vol 77 (1) ◽  
pp. 405-420 ◽  
Author(s):  
Kelvin E. Jones ◽  
Parveen Bawa
Keyword(s):  
Computer Simulation ◽  
Firing Rate ◽  
Time Course ◽  
Current Model ◽  
Response Probability ◽  
Muscle Spindles ◽  
Excitatory Postsynaptic Potential ◽  
Biophysical Properties ◽  
Rhythmic Firing ◽  
The Relationship

Jones, Kelvin E. and Parveen Bawa. Computer simulation of the responses of human motoneurons to composite 1A EPSPS: effects of background firing rate. J. Neurophysiol. 77: 405–420, 1997. Two compartmental models of spinal alpha motoneurons were constructed to explore the relationship between background firing rate and response to an excitatory input. The results of these simulations were compared with previous results obtained from human motoneurons and discussed in relation to the current model for repetitively firing human motoneurons. The morphologies and cable parameters of the models were based on two type-identified cat motoneurons previously reported in the literature. Each model included five voltage-dependent channels that were modeled using Hodgkin-Huxley formalism. These included fast Na+ and K+ channels in the initial segment and fast Na+ and K+ channels as well as a slow K+ channel in the soma compartment. The density and rate factors for the slow K+ channel were varied until the models could reproduce single spike AHP parameters for type-identified motoneurons in the cat. Excitatory synaptic conductances were distributed along the equivalent dendrites with the same density described for la synapses from muscle spindles to type-identified cat motoneurons. Simultaneous activation of all synapses on the dendrite resulted in a large compound excitatory postsynaptic potential (EPSP). Brief depolarizing pulses injected into a compartment of the equivalent dendrite resulted in pulse potentials (PPs), which resembled the compound EPSPs. The effects of compound EPSPs and PPs on firing probability of the two motoneuron models were examined during rhythmic firing. Peristimulus time histograms, constructed between the stimulus and the spikes of the model motoneuron, showed excitatory peaks whose integrated time course approximated the time course of the underlying EPSP or PP as has been shown in cat motoneurons. The excitatory peaks were quantified in terms of response probability, and the relationship between background firing rate and response probability was explored. As in real human motoneurons, the models exhibited an inverse relationship between response probability and background firing rate. The biophysical properties responsible for the relationship between response probability and firing rate included the shapes of the membrane voltage trajectories between spikes and nonlinear changes in PP amplitude during the interspike interval at different firing rates. The results from these simulations suggest that the relationship between response probability and background firing rate is an intrinsic feature of motoneurons. The similarity of the results from the models, which were based on the properties of cat motoneurons, and those from human motoneurons suggests that the biophysical properties governing rhythmic firing in human motoneurons are similar to those of the cat.

scholarly journals Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve membrane synchrony

2018 ◽  
Author(s):  
Richard Dewell ◽  
Fabrizio Gabbiani
Keyword(s):  
Synaptic Input ◽  
Collision Detection ◽  
Dendritic Morphology ◽  
Synaptic Integration ◽  
Neuronal Membrane ◽  
Hcn Channels ◽  
Movement Detector ◽  
Membrane Impedance ◽  
Wide Range

Brains processes information through the coordinated efforts of billions of individual neurons, each encoding a small part of the overall information stream. Central to this is how neurons integrate and transform complex patterns of synaptic inputs. The neuronal membrane impedance sets the gain and timing for synaptic integration, determining a neuron's ability to discriminate between synaptic input patterns. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper, Schistocerca americana. We examined how the cellular properties of the lobula giant movement detector (LGMD) neuron are tuned to enable the discrimination of synaptic input patterns key to its role in collision detection. We found that two common active conductances gH and gM, mediated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-type K+ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that the LGMD's branching morphology increased the gain and decreased delays associated with the mapping of synaptic input currents to membrane potential. We investigated whether other branching dendritic morphologies fulfill a similar function and found this to be true for a wide range of morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings further our understanding of the integration properties of individual neurons by showing the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.

scholarly journals Sparse bursts optimize information transmission in a multiplexed neural code

2018 ◽  
Vol 115 (27) ◽  
pp. E6329-E6338 ◽  
Author(s):  
Richard Naud ◽  
Henning Sprekeler
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Neural Code ◽  
Spike Timing ◽  
Neural Ensemble ◽  
Multiple Input ◽  
Cortical Hierarchy ◽  
Connectivity Patterns ◽  
Rate Coding

Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.

Resting and Active Properties of Pyramidal Neurons in Subiculum and CA1 of Rat Hippocampus

2000 ◽  
Vol 84 (5) ◽  
pp. 2398-2408 ◽  
Author(s):  
Nathan P. Staff ◽  
Hae-Yoon Jung ◽  
Tara Thiagarajan ◽  
Michael Yao ◽  
Nelson Spruston
Keyword(s):  
Action Potential ◽  
Action Potentials ◽  
Pyramidal Neurons ◽  
Current Injection ◽  
Synaptic Integration ◽  
Membrane Properties ◽  
Neuronal Membrane ◽  
Similar Action ◽  
Ca1 Neurons ◽  
Ca1 Pyramidal Neurons

Action potentials are the end product of synaptic integration, a process influenced by resting and active neuronal membrane properties. Diversity in these properties contributes to specialized mechanisms of synaptic integration and action potential firing, which are likely to be of functional significance within neural circuits. In the hippocampus, the majority of subicular pyramidal neurons fire high-frequency bursts of action potentials, whereas CA1 pyramidal neurons exhibit regular spiking behavior when subjected to direct somatic current injection. Using patch-clamp recordings from morphologically identified neurons in hippocampal slices, we analyzed and compared the resting and active membrane properties of pyramidal neurons in the subiculum and CA1 regions of the hippocampus. In response to direct somatic current injection, three subicular firing types were identified (regular spiking, weak bursting, and strong bursting), while all CA1 neurons were regular spiking. Within subiculum strong bursting neurons were found preferentially further away from the CA1 subregion. Input resistance ( R N), membrane time constant (τm), and depolarizing “sag” in response to hyperpolarizing current pulses were similar in all subicular neurons, while R N and τm were significantly larger in CA1 neurons. The first spike of all subicular neurons exhibited similar action potential properties; CA1 action potentials exhibited faster rising rates, greater amplitudes, and wider half-widths than subicular action potentials. Therefore both the resting and active properties of CA1 pyramidal neurons are distinct from those of subicular neurons, which form a related class of neurons, differing in their propensity to burst. We also found that both regular spiking subicular and CA1 neurons could be transformed into a burst firing mode by application of a low concentration of 4-aminopyridine, suggesting that in both hippocampal subfields, firing properties are regulated by a slowly inactivating, D-type potassium current. The ability of all subicular pyramidal neurons to burst strengthens the notion that they form a single neuronal class, sharing a burst generating mechanism that is stronger in some cells than others.

scholarly journals The Self and Its Prolonged Intrinsic Neural Timescale in Schizophrenia

2020 ◽  
Author(s):  
Georg Northoff ◽  
Karl Erik Sandsten ◽  
Julie Nordgaard ◽  
Troels Wesenberg Kjaer ◽  
Josef Parnas
Keyword(s):  
Negative Symptoms ◽  
Temporal Integration ◽  
The Self ◽  
Auditory Oddball ◽  
Power Law Exponent ◽  
Moderation Model ◽  
Relationship Of ◽  
The Relationship ◽  
Self Reference ◽  
Self Disorder

Abstract Schizophrenia (SCZ) can be characterized as a basic self-disorder that is featured by abnormal temporal integration on phenomenological (experience) and psychological (information processing) levels. Temporal integration on the neuronal level can be measured by the brain’s intrinsic neural timescale using the autocorrelation window (ACW) and power-law exponent (PLE). Our goal was to relate intrinsic neural timescales (ACW, PLE), as a proxy of temporal integration on the neuronal level, to temporal integration related to self-disorder on psychological (Enfacement illusion task in electroencephalography) and phenomenological (Examination of Anomalous Self-Experience [EASE]) levels. SCZ participants exhibited prolonged ACW and higher PLE during the self-referential task (Enfacement illusion), but not during the non-self-referential task (auditory oddball). The degree of ACW/PLE change during task relative to rest was significantly reduced in self-referential task in SCZ. A moderation model showed that low and high ACW/PLE exerted differential impact on the relationship of self-disorder (EASE) and negative symptoms (PANSS). In sum, we demonstrate abnormal prolongation in intrinsic neural timescale during self-reference in SCZ including its relation to basic self-disorder and negative symptoms. Our results point to abnormal relation of self and temporal integration at the core of SCZ constituting a “common currency” of neuronal, psychological, and phenomenological levels.

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