Selective Adaptation in Networks of Cortical Neurons

1999

Cortical neurons recorded in vivo exhibit highly variable responses to the repeated presentation of the same stimulus. To further understand the cellular mechanisms underlying this phenomenon, we performed intracellular recordings from neurons in cat striate cortex in vivo and examined the relationships between spontaneous activity and visually evoked responses. Activity was assessed on a trial-by-trial basis by measuring the membrane potential (V m ) fluctuations and spike activity during brief epochs immediately before and after the onset of an evoked response. We found that the response magnitude, expressed as a change in V m relative to baseline, was linearly correlated with the preceding spontaneous V m . This correlation was enhanced when the cells were hyperpolarized to reduce the activation of voltage-gated conductances. The output of the cells, expressed as spike counts and latencies, was only moderately correlated with fluctuations in the preceding spontaneous V m . Spike-triggered averaging of V m revealed that visually evoked action potentials arise from transient depolarizations having a rise time of ϳ10 msec. Consistent with this, evoked spike count was found to be linearly correlated with the magnitude of V m fluctuations in the ␥ (20-70 Hz) frequency band. We also found that the threshold of visually evoked action potentials varied over a range of ϳ10 mV. Examination of simultaneously recorded intracellular and extracellular activity revealed a correlation between V m depolarization and spike discharges in adjacent cells. Together these results demonstrate that response variability is attributable largely to coherent fluctuations in cortical activity preceding the onset of a stimulus, but also to variations in action potential threshold and the magnitude of high-frequency fluctuations evoked by the stimulus.

Single neocortical neurons are driven by populations of excitatory inputs, forming the basis of neural selectivity to features of sensory input. Excitatory connections are thought to mature during development through activity-dependent Hebbian plasticity1, whereby similarity between presynaptic and postsynaptic activity selectively strengthens some synapses and weakens others2. Evidence in support of this process ranges from measurements of synaptic ultrastructure to slice and in vivo physiology and imaging studies3,4,5,6,7,8. These corroborating lines of evidence lead to the prediction that a small number of strong synaptic inputs drive neural selectivity, while weak synaptic inputs are less correlated with the functional properties of somatic output and act to modulate activity overall6,7. Supporting evidence from cortical circuits, however, has been limited to measurements of neighboring, connected cell pairs, raising the question of whether this prediction holds for the full pro...

Journal of Neuroscience Methods, 2012

It is widely accepted that through a process of adaptation cells adjust their sensitivity in accordance with prevailing stimulus conditions. However, in two recent studies exploring adaptation in the rodent inferior colliculus and somatosensory cortex, neurons did not adapt towards global mean, but rather became most sensitive to inputs that were located towards the edge of the stimulus distribution with greater intensity than the mean. We reexamined electrophysiological data from the somatosensory study with the purpose of exploring the underlying encoding strategies. We found that neural gain tended to decrease as stimulus variance increased. Following adaptation to changes in global mean, neuronal output was scaled such that the relationship between firing rate and local, rather than global, differences in stimulus intensity was maintained. The majority of cells responded to large, positive deviations in stimulus amplitude; with a small number responding to both positive and negative changes in stimulus intensity. Adaptation to global mean was replicated in a model neuron by incorporating both spike-rate adaptation and tonic-inhibition, which increased in proportion to stimulus mean. Adaptation to stimulus variance was replicated by approximating the output of a population of neurons adapted to global mean and using it to drive a layer of recurrently connected depressing synapses. Within the barrel cortex, adaptation ensures that neurons are able to encode both overall levels of variance and large deviations in the input. This is achieved through a combination of gain modulation and a shift in sensitivity to intensity levels that are greater than the mean.

Journal of computational neuroscience, 2015

Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulation of the activity and gain control. The effects of adaptation have already been studied at the single-cell level, resulting from either voltage or calcium gated channels both activated by the spiking activity and modulating the dynamical responses of the neurons. In this study, by disentangling those effects into a linear (sub-threshold) and a non-linear (supra-threshold) part, we focus on the the functional role of those two distinct components of adaptation onto the neuronal activity at various scales, starting from single-cell responses up to recurrent networks dynamics, and under stationary or non-stationary stimulations. The effects of slow currents on collective dynamics, like modulation of population oscillation and reliability of...

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuationdriven dynamics despite structural heterogeneity in cortical circuits.

Journal of Neurophysiology, 2012

Variable responses of neuronal networks to repeated sensory or electrical stimuli reflect the interaction of the stimulus' response with ongoing activity in the brain and its modulation by adaptive mechanisms, such as cognitive context, network state, or cellular excitability and synaptic transmission capability. Here, we focus on reliability, length, delays, and variability of evoked responses with respect to their spatial distribution, interaction with spontaneous activity in the networks, and the contribution of GABAergic inhibition. We identified network-intrinsic principles that underlie the formation and modulation of spontaneous activity and stimulus-response relations with the use of state-dependent stimulation in generic neuronal networks in vitro. The duration of spontaneously recurring network-wide bursts of spikes was best predicted by the length of the preceding interval. Length, delay, and structure of responses to identical stimuli systematically depended on stimu...

Journal of Neurophysiology, 2012

Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CCH, Gerstner W. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. Cortical information processing originates from the exchange of action potentials between many cell types. To capture the essence of these interactions, it is of critical importance to build mathematical models that reflect the characteristic features of spike generation in individual neurons. We propose a framework to automatically extract such features from current-clamp experiments, in particular the passive properties of a neuron (i.e., membrane time constant, reversal potential, and capacitance), the spike-triggered adaptation currents, as well as the dynamics of the action potential threshold. The stochastic model that results from our maximum likelihood approach accurately predicts the spike times, the subthreshold voltage, the firing patterns, and the type of frequency-current curve. Extracting the model parameters for three cortical cell types revealed that cell types show highly significant differences in the time course of the spike-triggered currents and moving threshold, that is, in their adaptation and refractory properties but not in their passive properties. In particular, GABAergic fast-spiking neurons mediate weak adaptation through spike-triggered currents only, whereas regular spiking excitatory neurons mediate adaptation with both moving threshold and spike-triggered currents. GABAergic nonfast-spiking neurons combine the two distinct adaptation mechanisms with reduced strength. Differences between cell types are large enough to enable automatic classification of neurons into three different classes. Parameter extraction is performed for individual neurons so that we find not only the mean parameter values for each neuron type but also the spread of parameters within a group of neurons, which will be useful for future large-scale computer simulations.

Eprint Arxiv 1210 7165, 2012

Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus representation in the later stages of cortical sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in a network with adapting neurons. We find that cellular adaptation plays a critical role in the transient reduction of the trial-by-trial variability of cortical spiking, providing an explanation for a wide-spread and hitherto unexplained phenomenon by a simple mechanism. In insect olfaction, cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body, independent of inhibitory mechanisms. Our results reveal a computational principle that relates neuronal firing rate adaptation to temporal sparse coding and variability suppression in nervous systems with a sequential processing architecture.

India is a country of many religions, faiths, festivals and events. Owing to its around 1.2 billion populations, there are mass gathering events being organized at various levels involving large number of people. Chhath festival has a powerful grip and value on the religious structure of Bihar. People have strong belief for this festival. Most of the devotees believe that chhath festival gives them an internal energy and also helps in establishing an essence of spiritual communication among them and connects them with God. Spirituality is a broad concept, considered by some to be indefinable because it means something different for each individual. Many regard spirituality as an internal process concerned with finding purpose and meaning in life and some see it as communication with a higher power, with an inner power, with each other, with the earth or with a universal energetic force. The study is done through survey method in terms of descriptive explanations. The research area of the proposed study is Motihari and its nearby area of Bihar state. A sample of 100 chhath devotees is selected through purposive sampling method. Keyword: Chhath festival, spiritual communication, religious identities, beliefs.

Chichén Itzá (Jukatek Maji: Chi'ch'èen Ìitsha' pomeni »pri ustju vodnjaka Itza«) je bilo veliko mesto v predkolumbovski dobi, ki ga je zgradila civilizacija Majev. Arheološko najdišče se nahaja v občini Tinum, v zvezni državi Jukatan v Mehiki. Stopničaste piramide, templji, stebrne arkade in druge kamnite strukture Chichen Itze so bili svet Majev, ki so imeli tukaj urbano središče svojega imperija od 750 do 1200 našega štetja. Najbolj prepoznavna zgradba je Kukulkanov tempelj, znan tudi kot El Castillo. Ta veličastna stopničasta piramida prikazuje natančnost in pomembnost astronomije v življenju Majev in velik vpliv Toltekov, ki so se naselili okoli leta 1000 in združili dve kulturni tradiciji. Tempelj ima 365 stopnic po eno za vsak dan v letu. Vsak od štirih strani ima 91 stopnic in