Inhibitory synchrony as a mechanism for attentional gain modulation

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neuron's firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. The model suggest that the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.Comment: J.Physiology (Paris) in press, 11 figure

Neurosystems: brain rhythms and cognitive processing

Neuronal rhythms are ubiquitous features of brain dynamics, and are highly correlated with cognitive processing. However, the relationship between the physiological mechanisms producing these rhythms and the functions associated with the rhythms remains mysterious. This article investigates the contributions of rhythms to basic cognitive computations (such as filtering signals by coherence and/or frequency) and to major cognitive functions (such as attention and multi-modal coordination). We offer support to the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations.098352 - Wellcome Trust; 5R01NS067199 - NINDS NIH HH

Spiking Dynamics during Perceptual Grouping in the Laminar Circuits of Visual Cortex

Grouping of collinear boundary contours is a fundamental process during visual perception. Illusory contour completion vividly illustrates how stable perceptual boundaries interpolate between pairs of contour inducers, but do not extrapolate from a single inducer. Neural models have simulated how perceptual grouping occurs in laminar visual cortical circuits. These models predicted the existence of grouping cells that obey a bipole property whereby grouping can occur inwardly between pairs or greater numbers of similarly oriented and co-axial inducers, but not outwardly from individual inducers. These models have not, however, incorporated spiking dynamics. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity to inducer configurations occur despite irregularities in spike timing across all the interacting cells. Other models have demonstrated spiking dynamics in laminar neocortical circuits, but not how perceptual grouping occurs. The current model begins to unify these two modeling streams by implementing a laminar cortical network of spiking cells whose intracellular temporal dynamics interact with recurrent intercellular spiking interactions to quantitatively simulate data from neurophysiological experiments about perceptual grouping, the structure of non-classical visual receptive fields, and gamma oscillations.CELEST, an NSF Science of Learning Center (SBE-0354378); SyNAPSE program of the Defense Advanced Research Project Agency (HR001109-03-0001); Defense Advanced Research Project Agency (HR001-09-C-0011

Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others failed to find significant synchronization levels in such tasks. We attempt to understand both lines of evidence within a coherent theoretical framework. We conceptualize synchronization as an independent control parameter to study how the postsynaptic neuron transmits the average firing activity of a presynaptic population, in the presence of synchronization. We apply the Berger-Levy theory of energy efficient information transmission to interpret simulations of a Hodgkin-Huxley-type postsynaptic neuron model, where we varied the firing rate and synchronization level in the presynaptic population independently. We find that for a fixed presynaptic firing rate the simulated postsynaptic interspike interval distribution depends on the synchronization level and is well-described by a generalized extreme value distribution. For synchronization levels of 15% to 50%, we find that the optimal distribution of presynaptic firing rate, maximizing the mutual information per unit cost, is maximized at ~30% synchronization level. These results suggest that the statistics and energy efficiency of neuronal communication channels, through which the input rate is communicated, can be dynamically adapted by the synchronization level.Comment: 47 pages, 14 figures, 2 Table

Establishing Communication between Neuronal Populations through Competitive Entrainment

The role of gamma frequency oscillation in neuronal interaction, and the relationship between oscillation and information transfer between neurons, has been the focus of much recent research. While the biological mechanisms responsible for gamma oscillation and the properties of resulting networks are well studied, the dynamics of changing phase coherence between oscillating neuronal populations are not well understood. To this end we develop a computational model of competitive selection between multiple stimuli, where the selection and transfer of population-encoded information arises from competition between converging stimuli to entrain a target population of neurons. Oscillation is generated by Pyramidal-Interneuronal Network Gamma through the action of recurrent synaptic connections between a locally connected network of excitatory and inhibitory neurons. Competition between stimuli is driven by differences in coherence of oscillation, while transmission of a single selected stimulus is enabled between generating and receiving neurons via Communication-through-Coherence. We explore the effect of varying synaptic parameters on the competitive transmission of stimuli over different neuron models, and identify a continuous region within the parameter space of the recurrent synaptic loop where inhibition-induced oscillation results in entrainment of target neurons. Within this optimal region we find that competition between stimuli of equal coherence results in model output that alternates between representation of the stimuli, in a manner strongly resembling well-known biological phenomena resulting from competitive stimulus selection such as binocular rivalry

Relating macroscopic measures of brain activity to fast dynamic neuronal interactions

The aim of this thesis was to find a systematic relationship between neuronal synchrony and firing rates, that would enable us to make inferences about one given knowledge of the other. Functional neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), are sensitive to changes in overall population synaptic activity, that can be interpreted in terms of rate coding for a particular stimulus or task. Characterising the relationship between synchrony and firing rates would facilitate inferences about fast neuronal interactions on the basis of macroscopic measures such as those obtained by fMRI. In this thesis, we used computer simulations of neuronal networks and fMRI in humans to investigate the relationship between mean synaptic activity and fast synchronous neuronal interactions. We found that the extent to which different neurons engage in fast dynamic interactions is largely dependent on the neuronal population firing rates and vice versa, i.e. as one metric changes (either activity or synchrony), so does the other. Additionally, as a result of the strong coupling between overall activity and neuronal synchrony, there is also a robust relationship between background activity and stimulus-evoked activity: Increased background activity increases the gain of the neurons, by decreasing effective membrane time constants, and enhancing stimulus-evoked population activity through the selection of fast synchronous dynamics. In concluding this thesis, we tested and confirmed, with fMRI in humans, that this mechanism may account for attentional modulation, i.e. the change in baseline neuronal firing rates associated with attention, in cell assemblies selectively responding to an attended sensory attribute, enhances responses elicited by presentation of that attribute

Mechanisms for Phase Shifting in Cortical Networks and their Role in Communication through Coherence

In the primate visual cortex, the phase of spikes relative to oscillations in the local field potential (LFP) in the gamma frequency range (30–80 Hz) can be shifted by stimulus features such as orientation and thus the phase may carry information about stimulus identity. According to the principle of communication through coherence (CTC), the relative LFP phase between the LFPs in the sending and receiving circuits affects the effectiveness of the transmission. CTC predicts that phase shifting can be used for stimulus selection. We review and investigate phase shifting in models of periodically driven single neurons and compare it with phase shifting in models of cortical networks. In a single neuron, as the driving current is increased, the spike phase varies systematically while the firing rate remains constant. In a network model of reciprocally connected excitatory (E) and inhibitory (I) cells phase shifting occurs in response to both injection of constant depolarizing currents and to brief pulses to I cells. These simple models provide an account for phase-shifting observed experimentally and suggest a mechanism for implementing CTC. We discuss how this hypothesis can be tested experimentally using optogenetic techniques

Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: gamma-range synchronization between sensory and executive cortical areas

[EN] In this computational work, we investigated gamma-band synchronization across cortical circuits associated with selective attention. The model explicitly instantiates a reciprocally connected loop of spiking neurons between a sensory-type (area MT) and an executive-type (prefrontal/parietal) cortical circuit (the source area for top-down attentional signaling). Moreover, unlike models in which neurons behave as clock-like oscillators, in our model single-cell firing is highly irregular (close to Poisson), while local field potential exhibits a population rhythm. In this "sparsely synchronized oscillation" regime, the model reproduces and clarifies multiple observations from behaving animals. Top-down attentional inputs have a profound effect on network oscillatory dynamics while only modestly affecting single-neuron spiking statistics. In addition, attentional synchrony modulations are highly selective: interareal neuronal coherence occurs only when there is a close match between the preferred feature of neurons, the attended feature, and the presented stimulus, a prediction that is experimentally testable. When interareal coherence was abolished, attention-induced gain modulations of sensory neurons were slightly reduced. Therefore, our model reconciles the rate and synchronization effects, and suggests that interareal coherence contributes to large-scale neuronal computation in the brain through modest enhancement of rate modulations as well as a pronounced attention-specific enhancement of neural synchrony.This work was funded by the Volkswagen Foundation, the Spanish Ministry of Science and Innovation, and the European Regional Development Fund. A.C. is supported by the Researcher Stabilization Program of the Health Department of the Generalitat de Catalunya. X.-J.W. is supported by the National Institutes of Health Grant 2R01MH062349 and the Kavli Foundation. We are thankful to Stefan Treue for fruitful discussions and to Jorge Ejarque for technical support in efficiently implementing the search optimization procedure in a grid cluster computing system. Also, we thankfully acknowledge the computer resources and assistance from the Barcelona Supercomputing Center-Centro Nacional de Supercomputación, Spain.Ardid-Ramírez, JS.; Wang, X.; Gomez-Cabrero, D.; Compte, A. (2010). Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: gamma-range synchronization between sensory and executive cortical areas. Journal of Neuroscience. 30(8):2856-2870. https://doi.org/10.1523/JNEUROSCI.4222-09.2010S2856287030

Phasic cholinergic signaling promotes emergence of local gamma rhythms in excitatory–inhibitory networks

Recent experimental results have shown that the detection of cues in behavioral attention tasks relies on transient increases of acetylcholine (ACh) release in frontal cortex and cholinergically driven oscillatory activity in the gamma frequency band (Howe et al. Journal of Neuroscience, 2017, 37, 3215). The cue‐induced gamma rhythmic activity requires stimulation of M1 muscarinic receptors. Using biophysical computational modeling, we show that a network of excitatory (E) and inhibitory (I) neurons that initially displays asynchronous firing can generate transient gamma oscillatory activity in response to simulated brief pulses of ACh. ACh effects are simulated as transient modulation of the conductance of an M‐type K+ current which is blocked by activation of muscarinic receptors and has significant effects on neuronal excitability. The ACh‐induced effects on the M current conductance, gKs, change network dynamics to promote the emergence of network gamma rhythmicity through a Pyramidal‐Interneuronal Network Gamma mechanism. Depending on connectivity strengths between and among E and I cells, gamma activity decays with the simulated gKs transient modulation or is sustained in the network after the gKs transient has completely dissipated. We investigated the sensitivity of the emergent gamma activity to synaptic strengths, external noise and simulated levels of gKs modulation. To address recent experimental findings that cholinergic signaling is likely spatially focused and dynamic, we show that localized gKs modulation can induce transient changes of cellular excitability in local subnetworks, subsequently causing population‐specific gamma oscillations. These results highlight dynamical mechanisms underlying localization of ACh‐driven responses and suggest that spatially localized, cholinergically induced gamma may contribute to selectivity in the processing of competing external stimuli, as occurs in attentional tasks.Recent experiments showed that cholinergic signaling in the prefrontal cortex is fast and spatially localized in the context of attentional behavioral tasks. The cholinergic transients also generated gamma frequency oscillations that contributed to successful attentional performance. Using computational modeling, we show that transient cholinergic modulation of neural excitability induced the emergence of transient synchronous gamma activity from a background of asynchronous firing in excitatory–inhibitory neural networks.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162747/2/ejn14744.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162747/1/ejn14744_am.pd