Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
Predicting the Responses of Repetitively Firing Neurons to Current Noise  [PDF]
Charles J. Wilson ,David Barraza,Todd Troyer,Michael A. Farries
PLOS Computational Biology , 2014, DOI: doi/10.1371/journal.pcbi.1003612
Abstract: We used phase resetting methods to predict firing patterns of rat subthalamic nucleus (STN) neurons when their rhythmic firing was densely perturbed by noise. We applied sequences of contiguous brief (0.5–2 ms) current pulses with amplitudes drawn from a Gaussian distribution (10–100 pA standard deviation) to autonomously firing STN neurons in slices. Current noise sequences increased the variability of spike times with little or no effect on the average firing rate. We measured the infinitesimal phase resetting curve (PRC) for each neuron using a noise-based method. A phase model consisting of only a firing rate and PRC was very accurate at predicting spike timing, accounting for more than 80% of spike time variance and reliably reproducing the spike-to-spike pattern of irregular firing. An approximation for the evolution of phase was used to predict the effect of firing rate and noise parameters on spike timing variability. It quantitatively predicted changes in variability of interspike intervals with variation in noise amplitude, pulse duration and firing rate over the normal range of STN spontaneous rates. When constant current was used to drive the cells to higher rates, the PRC was altered in size and shape and accurate predictions of the effects of noise relied on incorporating these changes into the prediction. Application of rate-neutral changes in conductance showed that changes in PRC shape arise from conductance changes known to accompany rate increases in STN neurons, rather than the rate increases themselves. Our results show that firing patterns of densely perturbed oscillators cannot readily be distinguished from those of neurons randomly excited to fire from the rest state. The spike timing of repetitively firing neurons may be quantitatively predicted from the input and their PRCs, even when they are so densely perturbed that they no longer fire rhythmically.
Firing Patterns and Transitions in Coupled Neurons Controlled by a Pacemaker

LI Mei-Sheng,LU Qi-Shao,DUAN Li-Xia,WANG Qing-Yun,

中国物理快报 , 2008,
Abstract: To reveal the dynamics of neuronal networks with pacemakers, the firing patterns and their transitions are investigated in a ring HR neuronal network with gap junctions under the control of a pacemaker. Compared with the situation without pacemaker, the neurons in the network can exhibit various firing patterns as the external current is applied or the coupling strength of pacemaker varies. The results are beneficial for understanding the complex cooperative behaviour of large neural assemblies with pacemaker control.
Some Theoretical Properties of a Network of Discretely Firing Neurons  [PDF]
Stephen Luttrell
Computer Science , 2015,
Abstract: The problem of optimising a network of discretely firing neurons is addressed. An objective function is introduced which measures the average number of bits that are needed for the network to encode its state. When this is minimised, it is shown that this leads to a number of results, such as topographic mappings, piecewise linear dependence on the input of the probability of a neuron firing, and factorial encoder networks.
Information on mean, fluctuation and synchrony conveyed by a population of firing neurons  [PDF]
Hiode Hasegawa
Physics , 2007,
Abstract: A population of firing neurons is expected to carry not only mean firing rate but also its fluctuation and synchrony among neurons. In order to examine this possibility, we have studied responses of neuronal ensembles to three kinds of inputs: mean-, fluctuation- and synchrony-driven inputs. The generalized rate-code model including additive and multiplicative noise (H. Hasegawa, Phys. Rev. E {\bf 75}, 051904 (2007)) has been studied by direct simulations (DSs) and the augmented moment method (AMM) in which equations of motion for mean firing rate, fluctuation and synchrony are derived. Results calculated by the AMM are in good agreement with those by DSs. The independent component analysis (ICA) of our results has shown that mean firing rate, fluctuation (or variability) and synchrony may carry independent information in the population rate-code model. The input-output relation of mean firing rates is shown to have higher sensitivity for larger multiplicative noise, as recently observed in prefrontal cortex. A comparison is made between results obtained by the integrate-and-fire (IF) model and our rate-code model. The relevance of our results to experimentally obtained data is also discussed.
Firing Behavior and Network Activity of Single Neurons in Human Epileptic Hypothalamic Hamartoma  [PDF]
Peter N. Steinmetz,John F. Kerrigan
Frontiers in Neurology , 2013, DOI: 10.3389/fneur.2013.00210
Abstract: Objective: Human hypothalamic hamartomas (HH) are intrinsically epileptogenic and are associated with treatment-resistant gelastic seizures. The basic cellular mechanisms responsible for seizure onset within HH are unknown. We used intra-operative microwire recordings of single neuron activity to measure the spontaneous firing rate of neurons and the degree of functional connection between neurons within the tumor.
The firing rate of neurons in the nucleus cuneiformis in response to formalin in male rat
Abbas Haghparast,Amir-Mohammad Alizadeh,Fereshteh Motamedi
Physiology and Pharmacology , 2008,
Abstract: Introduction: Although formalin-induced activity in primary afferent fibers and spinal dorsal horn is well described, the midbrain neural basis underlying each phase of behavior in formalin test has not been clarified. The present study was designed to investigate the nucleus cuneiformis (CnF) neuronal responses during two phases after subcutaneous injection of formalin into the hind paw of rat. Materials & Methods: In this study, seventy six male NMRI adult rats, weighing 230-320 g were used. Control group (n=24), which was tested merely for determining spontaneous firing rate of CnF neurons. Saline group (n=15) which received saline (50μl; s.c.) instead of formalin into the plantar surface of hind paw after 15 min baseline recording. Formalin group that formalin-induced neural activity of 37 cells simultaneously recorded from the CnF during first phase (0-5 min) and second phase (15-60 min) of formalin test in 5-min intervals, using an extracellular single unit recording technique. Results: The baseline firing rate of neurons in the CnF varied between 1.2 and 39.2 spikes/sec and the average frequency of spontaneous activity over 1 h was 11.8 ± 1.1 spikes/sec. There were three neural clusters after formalin injection. Neurons in cluster 1 (46%) exhibited severe, transient excitatory response in the first (acute) phase while neurons in cluster 2 (35%) exhibited tonic but long-lasting excitatory response in the second (chronic) phase. Cluster 3, a small portion of neurons (about one fifth) which failed to show any evident responses to formalin test. Conclusion: Our findings suggest that alteration of neural activity and pattern in the spontaneous background of CnF neurons can be mediated a role in the transmission of nociceptive information induced by the peripheral injection of formalin and can be discussed in light of the role of these neurons in nociceptive information processing following peripheral stimuli.
Coding of odors by temporal binding within a model network of the locust antennal lobe  [PDF]
Mainak J. Patel,David Cai
Frontiers in Computational Neuroscience , 2013, DOI: 10.3389/fncom.2013.00050
Abstract: The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin–Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.
Corticostriatal Projection Neurons – Dichotomous Types and Dichotomous Functions  [PDF]
Anton Reiner,Natalie M. Hart,Wanlong Lei,Yunping Deng
Frontiers in Neuroanatomy , 2010, DOI: 10.3389/fnana.2010.00142
Abstract: The mammalian striatum receives its main excitatory input from the two types of cortical pyramidal neurons of layer 5 of the cerebral cortex – those with only intratelencephalic connections (IT-type) and those sending their main axon to the brainstem via the pyramidal tract (PT-type). These two neurons types are present in layer 5 of all cortical regions, and thus they appear to project together to all parts of striatum. These two neuron types, however, differ genetically, morphologically, and functionally, with IT-type neurons conveying sensory and motor planning information to striatum and PT-type neurons conveying an efference copy of motor commands (for motor cortex at least). Anatomical and physiological data for rats, and more recent data for primates, indicate that these two cortical neuron types also differ in their targeting of the two main types of striatal projection neurons, with the IT-type input preferentially innervating direct pathway neurons and the PT-type input preferentially innervating indirect pathway striatal neurons. These findings have implications for understanding how the direct and indirect pathways carry out their respective roles in movement facilitation and movement suppression, and they have implications for understanding the role of corticostriatal synaptic plasticity in adaptive motor control by the basal ganglia.
Selective serotonergic excitation of callosal projection neurons  [PDF]
Allan T. Gulledge
Frontiers in Neural Circuits , 2012, DOI: 10.3389/fncir.2012.00012
Abstract: Serotonin (5-HT) acting as a neurotransmitter in the cerebral cortex is critical for cognitive function, yet how 5-HT regulates information processing in cortical circuits is not well understood. We tested the serotonergic responsiveness of layer 5 pyramidal neurons (L5PNs) in the mouse medial prefrontal cortex (mPFC), and found three distinct response types: long-lasting 5-HT1A (1A) receptor-dependent inhibitory responses (84% of L5PNs), 5-HT2A (2A) receptor-dependent excitatory responses (9%), and biphasic responses in which 2A-dependent excitation followed brief inhibition (5%). Relative to 5-HT-inhibited neurons, those excited by 5-HT had physiological properties characteristic of callosal/commissural (COM) neurons that project to the contralateral cortex. We tested whether serotonergic responses in cortical pyramidal neurons are correlated with their axonal projection pattern using retrograde fluorescent labeling of COM and corticopontine-projecting (CPn) neurons. 5-HT generated excitatory or biphasic responses in all 5-HT-responsive layer 5 COM neurons. Conversely, CPn neurons were universally inhibited by 5-HT. Serotonergic excitation of COM neurons was blocked by the 2A antagonist MDL 11939, while serotonergic inhibition of CPn neurons was blocked by the 1A antagonist WAY 100635, confirming a role for these two receptor subtypes in regulating pyramidal neuron activity. Selective serotonergic excitation of COM neurons was not layer-specific, as COM neurons in layer 2/3 were also selectively excited by 5-HT relative to their non-labeled pyramidal neuron neighbors. Because neocortical 2A receptors are implicated in the etiology and pathophysiology of schizophrenia, we propose that COM neurons may represent a novel cellular target for intervention in psychiatric disease.
Firing Rate of Noisy Integrate-and-fire Neurons with Synaptic Current Dynamics  [PDF]
David Andrieux,Takaaki Monnai
Quantitative Biology , 2009, DOI: 10.1103/PhysRevE.80.021933
Abstract: We derive analytical formulae for the firing rate of integrate-and-fire neurons endowed with realistic synaptic dynamics. In particular we include the possibility of multiple synaptic inputs as well as the effect of an absolute refractory period into the description.
Page 1 /100
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.