Barrel cortical neurons and astrocytes coordinately respond to an increased whisker stimulus frequency
© Zhao et al.; licensee BioMed Central Ltd. 2012
Received: 21 March 2012
Accepted: 26 April 2012
Published: 26 April 2012
Nerve cells program the brain codes to manage well-organized cognitions and behaviors. It remains unclear how a population of neurons and astrocytes work coordinately to encode their spatial and temporal activity patterns in response to frequency and intensity signals from sensory inputs.
With two-photon imaging and electrophysiology to record cellular functions in the barrel cortex in vivo, we analyzed the activity patterns of neurons and astrocytes in response to whisker stimuli with increasing frequency, an environmental stimulus pattern that rodents experience in the accelerated motion. Compared to the resting state, whisker stimulation caused barrel neurons and astrocytes to be activated more synchronously. An increased stimulus frequency up-regulated the activity strength of neurons and astrocytes as well as coordinated their interaction. The coordination among the barrel neurons and astrocytes was fulfilled by increasing their functional connections.
Our study reveals that the nerve cells in the barrel cortex encode frequency messages in whisker tactile inputs through setting their activity coordination.
KeywordsNeuron Astrocyte Barrel cortex Whisker and two-photon cellular imaging
Brain functions are fulfilled by the activities of nerve cells [1–3]. The emerging evidences demonstrate that the neurons and astrocytes are involved in the information processing in the central nervous system [4–8]. Their communications are critical for the brain functions, such as the astrocytes are able to regulate the neuronal activities and plasticity [9–12]. However, how these neurons and astrocytes in local networks communicate coordinately to program the brain codes for well-organized cognition and behaviors remains unclear. The address of this issue helps to reveal the principles of information processing in the brain.
The studies by two-photon cellular imaging show that sensory stimuli, such as vision and auditory, activate the groups of neurons and astrocytes in sensory cortices [6, 8, 13–16]. Their temporal and spatial activity patterns in response to a single stimulation are well known [17–21]. In fact, the sensory inputs include the messages of frequency and intensity [22–25]. How the neurons and astrocytes in cortical networks coordinately work to recognize such messages in sensory inputs remains elucidated.
The nerve cells in the barrel cortex receive whisker tactile inputs [26–28], which is well used to study how the nerve cells in barrel cortical networks encode the whisker inputs. With the approaches of two-photon cellular imaging and electrophysiology in vivo, we examined the temporal and spatial activity patterns of barrel neurons and astrocytes in response to an increasing stimulus frequency to the whiskers, a common external stimulation when rodents explore their environments, such as the accelerated motion [23, 25]. By analyzing the magnitudes and temporal correlation of responses among the neurons and astrocytes, we found that neurons and astrocytes in barrel cortex coordinately respond to an increased whisker stimulus frequency.
The activity of barrel neurons rises in response to an increased frequency of whisker tactile input
By recording local field potentials (LFP) in the barrel cortex, we studied the responses of neurons to whisker stimuli in frequencies 8-to-12 Hz. Figure 1C illustrates a sweep of LFP signals (top trace) and the averaged LFP signals (bottom trace) induced by 8-to-12 Hz stimuli. The paired responses appear an increment pattern, i.e., response two is larger than response one. In statistical analysis, LFP amplitudes are significantly larger in response to 12 Hz stimuli than to 8 Hz ones (p < 0.05; Figure 1D).
As an increasing frequency of stimulus-to-whisker makes neuronal responses enhanced, the network neurons discriminate the increases of input frequency through strengthening their responsiveness. How the neurons and astrocytes in the barrel cortex coordinately respond to the frequency messages was analyzed by two-photon calcium imaging in vivo.
Neurons and astrocytes in barrel networks are coordinately activated by whisker tactile inputs
We further analyzed how neurons and astrocytes in the barrel cortex coordinately respond to frequency messages in whisker tactile inputs by measuring their spatial and temporal activities. This analysis is based on the data that the astrocytes in the brain regulate neuronal excitability and synaptic functions [34–36].
Barrel neurons and astrocytes increase their activity strength in response to high frequency input
In the study of the coordinate responses of neurons and astrocytes to frequency messages in whisker tactile inputs, we compared the changes of their activity strength induced by pair burst-stimuli to whiskers in frequencies 8-to-12 Hz (each burst for 10 sec. and inter-burst intervals in 10 sec.). Response one (R1) was corresponding to 8 Hz stimulus, and response two (R2) was a response to 12 Hz. Compared to control (8-to-8 Hz) in Additional file 1: Figure S1 ~ Additional file 2: Figure S 2, an increased stimulus frequency appears to enhance the responsive strength in the neurons and astrocytes.
We have calculated the ratio of increment portion to decrement one to estimate whether the responses of neurons and astrocytes to frequency-increased stimuli are parallel. As showed in Figure 3E, these ratios for neurons and astrocytes are not difference (p = 0.558). A parallel increase in the response strength of neurons and astrocytes indicates that the neurons and astrocytes in the barrel cortex coordinately respond to frequency messages in whisker tactile inputs.
Barrel neurons and astrocytes synchronize their activities in response to high frequency input
An example in Figure 4A ~ B shows cross-correlations among neuron-pairs in response to burst-pulse one (8 Hz) and two (12 Hz). Correlation coefficients in central peaks averaged from all of the experiments (n = 5) increase from 0.75 ± 0.04 for 8 Hz stimuli to 0.80 ± 0.03 for 12 Hz (p < 0.05, Figure 4C). Neuronal activity synchrony corresponding to high frequency stimuli indicates that barrel neurons discriminate input frequency changes by setting their synchrony.
Figure 4D ~ E shows an example that correlation coefficients among astrocyte-pairs increase in response to 8 Hz-to-12 Hz. The peak values of the correlogram for 8 Hz stimuli vs. 12 Hz ones are 0.92 ± 0.04 and 0.96 ± 0.03, respectively (p < 0.05, Figure 4F). The activity synchrony among the astrocytes in response to high frequency stimuli indicates that the barrel astrocytes modify their activity synchrony to encode the frequency message in whisker tactile inputs.
It is noteworthy that cells’ responses in barrel cortex to pair-stimuli in the same frequency (8-to-8 Hz) demonstrate decrement and less synchrony (Figures S1 ~ S2). The result does not support a possibility that the increment and synchrony in their responses to stimulus two at 12 Hz are due to repetitive stimulation. Moreover, the parameters used to quantify active strength and synchrony are not affected by the interval of two stimuli in barrel neurons ( Additional file 3: Figure S3).
The neurons and astrocytes coordinately encode the frequency message in whisker tactile inputs
Barrel neurons and astrocytes are synchronously activated by whisker tactile inputs (Figure 2C). The spatial and temporal patterns of barrel neurons and astrocytes are similar in response to frequency signals in whisker stimulations (Figures 3~4). We further examined whether the neurons and astrocytes in the barrel cortex coordinately encoded the frequency signals.
The change of functional connections among nerve cells is involved in encoding input frequencies
Cellular mechanisms for barrel neurons and astrocytes coordinately to encode frequency messages in whisker tactile inputs is likely founded on the dynamical changes in their functional connections. If it is a case, the functional connections among nerve cells should be upregulated in response to an increase of stimulus frequency. The functional connections among these cells were estimated by using their cross-correlations [37, 38]. Correlation coefficients during spontaneous activities at these nerve cells are set as no functional connections among them , and the averaged values above such coefficients plus two-time standard deviations are defined as the functional connections (Methods for details). Based on this principle, we analyzed the functional connections among neurons and astrocytes in the barrel cortex under the conditions of different input frequencies.
With two-photon cellular imaging and LFP recording in the barrel cortex in vivo, we have studied the processes for network cells to encode frequency messages in whisker tactile inputs. In response to an increase of input frequency, the portions of neurons and astrocytes with increment activity patterns are dominant and the activities of neurons and astrocytes are synchronized (Figures 1~4), as well as the coordinate interactions between neuronal network and astrocytic one are strengthened (Figure 5). The process for these cells to encode an increase of input frequency is likely fulfilled by increasing their functional connections (Figures 6~7). Thus, the neurons and astrocytes in the barrel cortex coordinately respond to the frequency messages in whisker tactile inputs through changing the strength of their functional connections. Whether this process is present in other sensory cortices remains to be examined.
In terms of the neural encoding, many studies have been done at individual neurons and synapses. Digital spikes encoded at the neurons and analogue signals at the synapses are essential codes in the brain [40–44]. As the brain functions are presumably fulfilled by neuronal networks [1–3], the studies in the activity patterns of network neurons have been paid attention [13, 16, 18, 45]. Their temporal and spatial activity patterns in response in a network to a single stimulus are known [14, 17–19, 21]. By giving stimuli in different frequencies, we reveal that nerve cells in the barrel cortex encode the frequency messages in whisker tactile inputs by resetting their functional connections as well as the portions of activity patterns and synchrony. Our findings provide the clues for understanding how neurons and astrocytes in the network coordinately program the brain codes for well-organized behaviors.
In the sensory systems, sequential stimuli in the same feature induce an adaptation in the sensations, and the increases in intensity or frequency should be given to elevate the sensitivity to these stimuli [46–48]. The changes in the ability of firing digital spikes at individual neurons are associated with the adaptation and sensitization [23, 49, 50]. It is not clear how the neurons and astrocytes integrated into neural networks encode these processes. Our studies demonstrate that pair-stimuli in the same frequency to whiskers make neurons and astrocytes to be lowered and asynchrony in their activities (Figures S1 ~ S2), and that an increasing stimulus frequency causes their responses to be increased and synchronized (Figures 2~4). The increment versus decrement and synchrony vs. asynchrony of nerve cells in response to sequential stimulations may be basic forms for encoding frequency signals and for the adaptation vs. sensitization. Their conversions may be involved in reading out the detail messages in natural sensory inputs.
The astrocytes presumably provide a micro-environment for the neurons to be functional [10, 35, 36, 51]. Studies by two-photon cellular imaging show that sensory stimuli induce a change of Ca2+ signal in astrocytes  and that Ca2+ dynamics in the neurons of barrel cortex are synchrony [4, 7]. The astrocytes play a crucial role in coupling neuronal organization to map signals in visual cortex . Beyond these findings, we show that spatial and temporal activities among astrocytes are coupling with neuronal activities in strength and synchrony to encode frequency messages in whisker tactile inputs, which is based on the dynamical change of their functional connections.
It is noteworthy that the responses of barrel neurons and astrocytes may be thought to be different in the anesthetized animals versus awaked ones [52, 53]. In our hypothesis, all responses of brain cells to stimulus intensity and frequency should be reduced in parallel from the anesthetized animals, compared to the awaked animals, such that the patterns of responses (i.e., response one versus response two) may not be changed. This hypothesis will be examined in our future studies.
Corresponding to an increase of whisker stimulus frequency, the neurons and astrocytes in the barrel cortex upregulate their activity strength, synchronize their activities and strengthen their functional connections. Therefore, the coordinate interactions among neurons and astrocytes in cortical networks are mechanistically involved in encoding the frequency messages in sensory inputs.
Animal surgery and fluorescence labeling
The study and all experiments conducted were fully approved by the Institutional Animal Care Unit Committee (IACUC) in Administration Office of Laboratory Animals Beijing China (ID# B10831). FVB mice in postnatal days (PND) 20 ~ 35 were anesthetized by the intraperitoneal injections of urethane (1.5 g/kg). Anesthetic depth was judged based on lack of reflexes in pinch withdrawal and blink eyelid, and was maintained by giving the supplemental dosage of urethane (0.25 g/kg) throughout the experiments. Body temperature was maintained by using a computer-controlled heating blanket at 37°C. The barrel cortex was located based on the distributional map of superficial vessels and confirmed by histological reconstructions (Figure 1A). A craniotomy (1 ~ 2 mm in diameter) was made on the skull above the center of the barrel cortex (Figure 1B), which was located at 1 mm posterior to the bregma and 3.5 mm lateral to the midline. It is noteworthy that the dura was intact throughout all experiments, and the care was taken to avoid any damage to superficial vessels and cortices.
In our studies, Oregon Green BAPTA-1-AM (OBG-1, Invitrogen, CA USA), a Ca2+ dye, was used to measure the activities from neurons and astrocytes. OGB-1 was dissolved in DMSO and 20% Pluronic F-127 (2 g Pluronic F-127 in 10 ml DMSO, Invitrogen, USA) to have its stock solution at 10 mM. The stock solution was diluted in ACSF to yield its final concentration at 1 mM. This OBG-1 solution was injected into layer I ~ II of barrel cortex by the pressure (1 bar, 5 min) through a patch pipette (200 μm below the pia) to label the population of nerve cells, termed as multicell bolus loading [55–57]. In the meantime, 100 μM sulforhodanmine-101 (SR101, Invitrogen, USA) was co-injected to label the astrocytes specifically . The volumes of these dyes were controlled at ~0.5 μl. After micro-injections, the craniotomy well was filled by low-melted agarose (1 ~ 2%) in saline and then was sealed with glass coverslip. The exposed skull was adhered to a custom-made recording chamber with dental acrylic cement, which was surperfused with saline (mM): 125 NaCl, 2.5 KCl, 26 NaHCO3, 1.25 NaH2PO4, 2 CaCl2, 1 MgCl2, 20 glucose (pH 7.4). The saline was warmed up to 37°C and bubbled with 95%O2/5% CO2.
Two-photon cellular imaging
Calcium imaging experiments were done 1 hour after dye injection by using two-photon laser scanning confocal microscope (Olympus FV-1000, Tokyo, Japan). Two-photon laser-beam generator (Mai Tai, Physical Spectrum, USA) and scanning system were mounted onto an upright microscope (Olympus BX61WI) with water immersion objectives (IR-LUMPLan Fl, 0.8NA, 40X). Two-photon laser beam at 810 nm was given to excite OGB-1 and SR101. Average power delivered to the brain tissue was less than 75 mW. The emission wavelengths were 523 nm for Ca2+-binding OGB-1 and 603 nm for SR-101, respectively. Whole field images were acquired at 10 Hz frame rate (256 × 256 pixels). The parameters for laser beam and photomultiplier tube were locked for the measurements before and after different stimuli as well as throughout all experiments in order to have a consistent condition in the comparisons of the results.
Local field potential (LFP) recording
Local field potentials were recorded in layerII/III of barrel cortex by using a glass pipette that contained the standard pipette solution (150 mM NaCl, 2.5 mM KCl, 10 mM HEPES). The resistance of recording pipettes was ~10 MΩ. Electrical signals were inputted to an AxoClamp-2B amplifier and pClamp 10 system (Axon Instrument Inc. CA USA), in which Clampex was used for data acquisition and Clampfit for data analysis. The electrical signals were digitized at 10 kHz and band-pass filtered at 1 ~ 100 Hz. It is noteworthy that the LFP recording and two-photon cellular imaging were performed in the identical area of barrel cortex (Fig. 1A ~ B), which allowed us to study the processes of neural encoding in the barrel cortex by electrophysiology and cellular imaging.
Whisker stimuli and barrel cells’ responses
All major whiskers in the contralateral sides of the imaged barrel cortices were deflected in a caudal-to-rostral direction by air-puffing during the experiments, which is more similar to the natural movement of whiskers. Whisker stimuli were done by giving the sequential brief pulses of air-puffing (50 psi, 50 ms) through a tiny steel tube that was mounted on a micromanipulator and controlled with costume-made LabVIEW program. The stimulus patterns were the paired burst-pulses, in which each burst had a given frequency. The frequency patterns in these paired bursts (10 seconds for each) were 8 and 12 Hz (8-to-12 Hz), closely to natural frequency in exploratory whisking [25, 49, 58]. Burst-pulse intervals were 10 seconds. To avoid the stimulations to the skin and furs, a tip of the stimulator was positioned in a way that it did not blow on the snout.
The amplitudes of Ca2+ signals are correlated positively with spike frequency, and Ca2+ levels in a neuron indicate its functional activities, so that spiking activity at the neurons can be estimated from their somatic Ca2+ signals in vivo[19, 31, 32, 59]. Different from the spikes as a functional index of neuronal activity, the activities of astrocytes are associated with the changes of Ca2+ signals [30, 60]. In addition, the synchrony of Ca2+ signals provide a measurement for the timing of cellular activities [4, 7, 54, 61]. Therefore, we studied the activity patterns of barrel neurons and astrocytes in response to whisker stimuli by using in vivo two-photon cellular imaging in order to reveal the processes of neuronal encoding in brain networks, in which the peak amplitudes and temporal synchrony of Ca2+ signals were analyzed.
Ca2+ fluorescence signals for cellular responses to whisker stimuli were acquired by using Fluoviewer-10 software (Olympus Inc. Japan) and analyzed in the regions of interest (ROI) from cell bodies by using NIH ImageJ and MATLAB (MathWorks). To reduce the photon and PMT noise, a median filter (radius, 1 pixel) was applied to all images. Ca2+ signals in cellular responses were normalized and presented as relative fluorescence changes (ΔF/F)[29, 62, 63]. Baseline fluorescence (F) was an averaged value in the ROI before stimuli, and ΔF values were differences between Ca2+ signals from the evoked responses in the ROI and baseline fluorescence. It is noteworthy that all of the fluorescence signals were subtracted from the noise signals of unstained blood vessels, as well as Ca2+ signals in the astrocytes were normalized to SR101 signal to eliminate motion artefacts. The normalized Ca2+ signals were smoothed by low-pass Butterworth filter to remove low-amplitude fluctuations and to minimize the distortions from fast Ca2+ transients [31, 32]. Effective signals from each of active cells were judged according to a criterion that their relative fluorescence changes were greater than 2.5 SD of baseline values and lasted for 500 ms. In our experiments, whisker stimuli induced the robust changes of Ca2+ signals in barrel cells, and the criteria above was found effective for sorting evoked signals from noise.
In our study, the paired burst-stimuli were given to induce two sequential responses. As the fluctuation of fluorescence signals influenced a precise measurement of response amplitudes, we thought the magnitude differences of two responses if their differences were above 2 SD of baseline values; however, we defined no difference in the magnitude of two responses if their net changes were less than 2 SD. If cellular response one (R1) was larger than response two (R2) above 2 SD of baseline, the pattern was defined as the decrement (R1 > R2). On the other hand, R2 > R1 above 2 SD was the increment. No differences for R1 and R2 were called as parallel. This classification is similar to synaptic transmission patterns . It is noteworthy that R2 values were the absolute changes of responses induced by stimulus two. That is, if the calcium signals in response to stimulus one were not back to their baseline levels, R2 was measured as a difference between the magnitude of response two and the residual level of response one.
mx and my are the means of the corresponding series. Correlation coefficients normalized to the autocorrelation at zero lag were calculated. Based on these calculations, the correlation matrices were plotted using MATLAB 7.0.
It is noteworthy that the definition of functional connection, whose threshold is set at mean + 2SD of correlation coefficients during the spontaneous activities of network cells, is based on an assumption that their activities are random in nature (no coordination). In other words, there are no interactions, or functional connections, among these network cells without input signals .
Based on these criteria of binary adjacency matrices and the spatial positions of network cells, we plotted the graphs which consisted of a set of nodes (the cells activated by stimulus bursts) and their functional connections (lines) under the conditions of response one to 8 Hz stimuli and response two to 12 Hz. In these graphs of neural networks, two parameters for each cell were merited to indicate how each cell is connected with others. The cell that connects with one at least is called as a function-connected cell in neural network. The percentages of function-connceted cells present how many cells are functionally connected with others. If a cell connects with others, the percentages of functional connections for its actually connected cells in the total cells are calculated to present the connection strength for each of network cells. The folmula are given below.
For a neural network consisting of activated neurons (N) in complete graphs, the number of connctions for each neuron with others is N-1. The number of function-connected neurons is n, and the averaged number of connections for each neuron with others is k. Thus, P n = n/N stands for the percentages of function-connected neurons. P k = k/(N-1) presents the percentages of functional connections of each neuron. The astrocytes are connected tightly and widely via gap junctions, the number of connected neuron-astrocyte pairwise shows no variation during different stimuli in our studies. In a network comprising of N neurons and M astrocytes, we calculate the percentages of neuron-astrocytic functional connections (l) in total potential links, which is P l = l/(N∙M).
All data are presented as mean ± SEM. Student’s t tests (two-tailed, paired, or unpaired assuming unequal variances) were done in R software package, version 2.10.1 (http://www.r-project.org/) to evaluate statistical significance. A p ≤ 0.05 is defined as statistical significance.
We thank Dr. Keegan’s proof reading before the submission. This study is granted by National Award for Outstanding Young Scientist (30325021), Natural Science Foundation China (30990261, 81171033) and National Basic Research Program (2011CB504405) to JHW.
- Byrne JH: Learning and memory: basic mechanisms. Amsterdam: Academic; 2003.
- Kandel E, Schwartz J, Jessell T: Principles of Neural Science. 4th edition. New York: McGraw-Hill; 2000.
- Shepard GM: Neurobiology. Oxford: Oxford University Press; 1994.
- Hirase H, Qian L, Bartho P, Buzsaki G: Calcium dynamics of cortical astrocytic networks in vivo. PLoS Biol 2004, 2:E96.PubMedView Article
- Gourine AV, Kasymov V, Marina N, Tang F, Figueiredo MF, Lane S, Teschemacher AG, Spyer KM, Deisseroth K, Kasparov S: Astrocytes control breathing through pH-dependent release of ATP. Science 2010, 329:571–575.PubMedView Article
- Schummers J, Yu H, Sur M: Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science 2008, 320:1638–1643.PubMedView Article
- Takata N, Hirase H: Cortical layer 1 and layer 2/3 astrocytes exhibit distinct calcium dynamics in vivo. PLoS One 2008, 3:e2525.PubMedView Article
- Wang X, Lou N, Xu Q, Tian G-F, Peng WG, Han X, Kang J, Takano T, Nedergaard M: Astrocytic Ca2+ signaling evoked by sensory stimulation in vivo. Nat Neurosci 2006, 9:816–823.PubMedView Article
- Christopherson KS, Ullian EM, Stokes CC, Mullowney CE, Hell JW, Agah A, Lawler J, Mosher DF, Bornstein P, Barres BA: Thrombospondins are astrocyte-secreted proteins that promote CNS synaptogenesis. Cell 2005, 120:421–433.PubMedView Article
- Fellin T: Communication between neurons and astrocytes: relevance to the modulation of synaptic and network activity. J Neurochem 2009, 108:533–544.PubMedView Article
- Giaume C, Maravall M, Welker E, Bonvento G: The Barrel Cortex as a Model to Study Dynamic Neuroglial Interaction. Neuroscientist 2009, 15:351–366.PubMedView Article
- Haber M, Zhou L, Murai KK: Cooperative astrocyte and dendritic spine dynamics at hippocampal excitatory synapses. J Neurosci 2006, 26:8881–8891.PubMedView Article
- Gobel W, Helmchen F: In vivo calcium imaging of neural network function. Physiology (Bethesda) 2007, 22:358–365.View Article
- Ohki K, Chung S, Ch’ng YH, Kara P, Reid RC: Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 2005, 433:597–603.PubMedView Article
- Rochefort NL, Garaschuk O, Milos RI, Narushima M, Marandi N, Pichler B, Kovalchuk Y, Konnerth A: Sparsification of neuronal activity in the visual cortex at eye-opening. Proc Natl Acad Sci U S A 2009, : .
- Svoboda K, Yasuda R: Principles of two-photon excitation microscopy and its applications to neuroscience. Neuron 2006, 50:823–839.PubMedView Article
- Kerr JN, de Kock CP, Greenberg DS, Bruno RM, Sakmann B, Helmchen F: Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. J Neurosci 2007, 27:13316–13328.PubMedView Article
- Kerr JN, Greenberg D, Helmchen F: Imaging input and output of neocortical networks in vivo. Proc Natl Acad Sci U S A 2005, 102:14063–14068.PubMedView Article
- Sato TR, Gray NW, Mainen ZF, Svoboda K: The Functional Microarchitecture of the Mouse Barrel Cortex. PLoS Biol 2007, 5:e189.PubMedView Article
- Stettler DD, Axel R: Representations of odor in the piriform cortex. Neuron 2009, 63:854–864.PubMedView Article
- Winship IR, Plaa N, Murphy TH: Rapid astrocyte calcium signals correlate with neuronal activity and onset of the hemodynamic response in vivo. J Neurosci 2007, 27:6268–6272.PubMedView Article
- Ahl AS: The role of vibrissae in behavior: a status review. Vet Res Commun 1986, 10:245–268.PubMedView Article
- Melzer P, Sachdev RN, Jenkinson N, Ebner FF: Stimulus frequency processing in awake rat barrel cortex. J Neurosci 2006, 26:12198–12205.PubMedView Article
- Melzer P, Champney GC, Maguire MJ, Ebner FF: Rate code and temporal code for frequency of whisker stimulation in rat primary and secondary somatic sensory cortex. Exp Brain Res 2006, 172:370–386.PubMedView Article
- Moore CI: Frequency-dependent processing in the vibrissa sensory system. J Neurophysiol 2004, 91:2390–2399.PubMedView Article
- Petersen CC: The functional organization of the barrel cortex. Neuron 2007, 56:339–355.PubMedView Article
- Sato TR, Svoboda K: The functional properties of barrel cortex neurons projecting to the primary motor cortex. J Neurosci 2010, 30:4256–4260.PubMedView Article
- Svoboda K, Helmchen F, Denk W, Tank DW: Spread of dendritic excitation in layer 2/3 pyramidal neurons in rat barrel cortex in vivo. Nat Neurosci 1999, 2:65–73.PubMedView Article
- Cossart R, Ikegaya Y, Yuste R: Calcium imaging of cortical networks dynamics. Cell Calcium 2005, 37:451–457.PubMedView Article
- Di Garbo A, Barbi M, Chillemi S, Alloisio S, Nobile M: Calcium signalling in astrocytes and modulation of neural activity. Biosystems 2007, 89:74–83.PubMedView Article
- Moreaux L, Laurent G: Estimating firing rates from calcium signals in locust projection neurons in vivo. Front Neural Circuits 2007, 1:2.PubMedView Article
- Yaksi E, Friedrich RW: Reconstruction of firing rate changes across neuronal populations by temporally deconvolved Ca2+ imaging. Nat Methods 2006, 3:377–383.PubMedView Article
- Nimmerjahn A, Kirchhoff F, Kerr JN, Helmchen F: Sulforhodamine 101 as a specific marker of astroglia in the neocortex in vivo. Nat Methods 2004, 1:31–37.PubMedView Article
- Lin SC, Bergles DE: Synaptic signaling between neurons and glia. Glia 2004, 47:290–298.PubMedView Article
- Schipke CG, Kettenmann H: Astrocyte responses to neuronal activity. Glia 2004, 47:226–232.PubMedView Article
- Vernadakis A: Glia-neuron intercommunications and synaptic plasticity. Prog Neurobiol 1996, 49:185–214.PubMedView Article
- Cho MW, Choi MY: Brain Networks: Graph Theoretical Analysis and Development Models. Int J Imag Syst Tech 2010, 20:108–116.View Article
- Foldy C, Dyhrfjeld-Johnsen J, Soltesz I: Structure of cortical microcircuit theory. J Physiol 2005, 562:47–54.PubMedView Article
- Ringach DL: Spontaneous and driven cortical activity: implications for computation. Curr Opin Neurobiol 2009, 19:439–444.PubMedView Article
- Abbott LF, Regehr WG: Synaptic computation. Nature 2004, 431:796–803.PubMedView Article
- Chen N, Chen X, Wang JH: Homeostasis established by coordination of subcellular compartment plasticity improves spike encoding. J Cell Sci 2008, 121:2961–2971.PubMedView Article
- Chen N, Yu J, Qian H, Ge R, Wang JH: Axons amplify somatic incomplete spikes into uniform amplitudes in mouse cortical pyramidal neurons. PLoS One 2010, 5:e11868.PubMedView Article
- Wang JH, Wei J, Chen X, Yu J, Chen N, Shi J: Gain and fidelity of transmission patterns at cortical excitatory unitary synapses improve spike encoding. J Cell Sci 2008, 121:2951–2960.PubMedView Article
- Yu J, Qian H, Chen N, Wang JH: Quantal glutamate release is essential for reliable neuronal encodings in cerebral networks. PLoS One 2011, 6:e25219.PubMedView Article
- Brecht M, Fee MS, Garaschuk O, Helmchen F, Margrie TW, Svoboda K, Osten P: Novel approaches to monitor and manipulate single neurons in vivo. J Neurosci 2004, 24:9223–9227.PubMedView Article
- Jones EG: Cortical and subcortical contributions to activity-dependent plasticity in primate somatosensory cortex. Annu Rev Neurosci 2000, 23:1–37.PubMedView Article
- Karwoski CJ, Proenza LM: Transient Adaptation and Sensitization in the Retina of Necturus. J Gen Physiol 1980, 76:479–497.PubMedView Article
- Teller DY, Gestrin PJ: Sensitization by Annular Surrounds . Sensitization and Dark Adaptation. Vision Res 1969, 9:1481–1489.PubMedView Article
- Kleinfeld D, Ahissar E, Diamond ME: Active sensation: insights from the rodent vibrissa sensorimotor system. Curr Opin Neurobiol 2006, 16:435–444.PubMedView Article
- Maravall M, Petersen RS, Fairhall AL, Arabzadeh E, Diamond ME: Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex. PLoS Biol 2007, 5:e19.PubMedView Article
- Newman EA: New roles for astrocytes: regulation of synaptic transmission. Trends Neurosci 2003, 26:536–542.PubMedView Article
- Hartings JA, Simons DJ: Thalamic relay of afferent responses to 1- to 12-Hz whisker stimulation in the rat. J Neurophysiol 1998, 80:1016–1019.PubMed
- Vijayan S, Hale GJ, Moore CI, Brown EN, Wilson M: Activity in the barrel cortex during active behavior and sleep. J Neurophysiol 2010, 103:2074–2084.PubMedView Article
- Golshani P, Goncalves JT, Khoshkhoo S, Mostany R, Smirnakis S, Portera-Cailliau C: Internally mediated developmental desynchronization of neocortical network activity. J Neurosci 2009, 29:10890–10899.PubMedView Article
- Garaschuk O, Milos RI, Konnerth A: Targeted bulk-loading of fluorescent indicators for two-photon brain imaging in vivo. Nat Protoc 2006, 1:380–386.PubMedView Article
- Golshani P, Portera-Cailliau C: In vivo 2-photon calcium imaging in layer 2/3 of mice. J Vis Exp 2008, 13:681.PubMed
- Stosiek C, Garaschuk O, Holthoff K, Konnerth A: In vivo two-photon calcium imaging of neuronal networks. Proc Natl Acad Sci U S A 2003, 100:7319–7324.PubMedView Article
- Ni H, Huang L, Chen N, Zhang F, Liu D, Ge M, Guan S, Zhu Y, Wang JH: Upregulation of barrel GABAergic neurons is associated with cross-modal plasticity in olfactory deficit. PLoS One 2010, 5:e13736.PubMedView Article
- Petersen OH, Michalak M, Verkhratsky A: Calcium signalling: past, present and future. Cell Calcium 2005, 38:161–169.PubMedView Article
- Halassa MM, Fellin T, Haydon PG: The tripartite synapse: roles for gliotransmission in health and disease. Trends Mol Med 2007, 13:54–63.PubMedView Article
- Smith SL, Hausser M: Parallel processing of visual space by neighboring neurons in mouse visual cortex. Nat Neurosci 2010, 13:1144–1149.PubMedView Article
- Stutzmann GE, Parker I: Dynamic multiphoton imaging: a live view from cells to systems. Physiology 2005, 20:15–21.PubMedView Article
- Knopfel T, Diez-Garcia J, Akemann W: Optical probing of neuronal circuit dynamics: genetically encoded versus classical fluorescent sensors. Trends Neurosci 2006, 29:160–166.PubMedView Article
- Ch’ng YH, Reid RC: Cellular imaging of visual cortex reveals the spatial and functional organization of spontaneous activity. Front Integr Neurosci 2010, 29:4.
- Deitmer JW, Verkhratsky AJ, Lohr C: Calcium signalling in glial cells. Cell Calcium 1998, 24:405–416.PubMedView Article
- Nedergaard M, Rodriguez JJ, Verkhratsky A: Glial calcium and diseases of the nervous system. Cell Calcium 2010, 47:140–149.PubMedView Article
- Eldawlatly S, Jin R, Oweiss KG: Identifying functional connectivity in large-scale neural ensemble recordings: a multiscale data mining approach. Neural Comput 2009, 21:450–477.PubMedView Article
- Sporns O: Small-world connectivity, motif composition, and complexity of fractal neuronal connections. Biosystems 2006, 85:55–64.PubMedView Article
- Zhou D, Thompson WK, Siegle G: MATLAB toolbox for functional connectivity. NeuroImage 2009, 47:1590–1607.PubMedView Article
- Sporns O: The non-random brain: efficiency, economy, and complex dynamics. Front Comput Neurosci 2011, 5:5.PubMedView Article
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.