Spatiotemporal Patterns Of Neuronal Activity Research Articles

Volumetric optoacoustic neurobehavioral tracking of epileptic seizures in freely-swimming zebrafish larvae.

Fast three-dimensional imaging of freely-swimming zebrafish is essential to understand the link between neuronal activity and behavioral changes during epileptic seizures. Studying the complex spatiotemporal patterns of neuronal activity at the whole-brain or -body level typically requires physical restraint, thus hindering the observation of unperturbed behavior. Here we report on real-time volumetric optoacoustic imaging of aberrant circular swimming activity and calcium transients in freely behaving zebrafish larvae, continuously covering their motion across an entire three-dimensional region. The high spatiotemporal resolution of the technique enables capturing ictal-like epileptic seizure events and quantifying their propagation speed, independently validated with simultaneous widefield fluorescence recordings. The work sets the stage for discerning functional interconnections between zebrafish behavior and neuronal activity for studying fundamental mechanisms of epilepsy and in vivo validation of treatment strategies.

A spatiotemporal increase of neuronal activity accompanies the motivational effect of wheel running in mice

Spatiotemporal patterns of neuronal activity underlying the motivational effect of rotating running wheels (RWs) in rodents remain largely undetermined. Here, we investigated changes of neuronal activity among brain regions associated with motivation across different intensities of motivation for RWs in mice. Daily exposure to RWs gradually increased rotation number, then became stable after approximately 3 weeks. Immunohistochemical analyses revealed that the number of c-Fos (a neuronal activity marker)-positive cells increased in the medial prefrontal cortex (mPFC), core and shell of the nucleus accumbens (NAc), dorsal striatum (Str), and lateral septum (LS) at day 1, day 9, and days 20–24, in a time-dependent manner. Additionally, despite exposure to locked RWs for over 7 days after establishing stable rotation with 3-week RW access, increased c-Fos expression was still observed in most of these brain areas. Furthermore, daily overnight RW access developed stable rotation by day 6, with high and low rotation numbers at the start and end of the overnight session, respectively. The number of c-Fos-positive cells at the start of RW rotation was significantly higher than at the end of RW rotation in most brain regions. Furthermore, after establishing stable rotation, the number of c-Fos-positive cells increased in the mPFC and shell of the NAc of mice that only observed RWs. These findings suggest that the subareas of the mPFC and NAc may be critically involved in the motivational effects of RW rotations.

Casting a Wide Net to Catch Seizures.

Network Properties Revealed During Multi-Scale Calcium Imaging of Seizure Activity in Zebrafish Liu J, Baraban SC. eNeuro. 2019;6(1):ENEURO.0041-19.2019. doi:10.1523/ENEURO.0041-19.2019. eCollection 2019 Jan-Feb. PMID: 30895220. Seizures are characterized by hypersynchronization of neuronal networks. Understanding these networks could provide a critical window for therapeutic control of recurrent seizure activity, that is, epilepsy. However, imaging seizure networks have largely been limited to microcircuits in vitro or small "windows" in vivo. Here, we combine fast confocal imaging of genetically encoded calcium indicator-expressing larval zebrafish with local field potential recordings to study epileptiform events at whole-brain and single-neuron levels in vivo. Using an acute seizure model (pentylenetetrazole, PTZ), we reliably observed recurrent electrographic ictal-like events associated with generalized activation of all major brain regions and uncovered a well-preserved anterior to posterior seizure propagation pattern. We also examined brain-wide network synchronization and spatiotemporal patterns of neuronal activity in the optic tectum microcircuit. Brain-wide and single-neuronal level analysis of PTZ-exposed and 4-aminopyridine-exposed zebrafish revealed distinct network dynamics associated with seizure and nonseizure hyperexcitable states, respectively. Neuronal ensembles, comprised of coactive neurons, were also uncovered during interictal-like periods. Taken together, these results demonstrate that macro- and micro-network calcium motifs in zebrafish may provide a greater understanding of epilepsy.

Network Properties Revealed during Multi-Scale Calcium Imaging of Seizure Activity in Zebrafish.

Seizures are characterized by hypersynchronization of neuronal networks. Understanding these networks could provide a critical window for therapeutic control of recurrent seizure activity, i.e., epilepsy. However, imaging seizure networks has largely been limited to microcircuits in vitro or small “windows” in vivo. Here, we combine fast confocal imaging of genetically encoded calcium indicator (GCaMP)-expressing larval zebrafish with local field potential (LFP) recordings to study epileptiform events at whole-brain and single-neuron levels in vivo. Using an acute seizure model (pentylenetetrazole, PTZ), we reliably observed recurrent electrographic ictal-like events associated with generalized activation of all major brain regions and uncovered a well-preserved anterior-to-posterior seizure propagation pattern. We also examined brain-wide network synchronization and spatiotemporal patterns of neuronal activity in the optic tectum microcircuit. Brain-wide and single-neuronal level analysis of PTZ-exposed and 4-aminopyridine (4-AP)-exposed zebrafish revealed distinct network dynamics associated with seizure and non-seizure hyperexcitable states, respectively. Neuronal ensembles, comprised of coactive neurons, were also uncovered during interictal-like periods. Taken together, these results demonstrate that macro- and micro-network calcium motifs in zebrafish may provide a greater understanding of epilepsy.

A statistical method for analyzing and comparing spatiotemporal cortical activation patterns

Information in the cortex is encoded in spatiotemporal patterns of neuronal activity, but the exact nature of that code still remains elusive. While onset responses to simple stimuli are associated with specific loci in cortical sensory maps, it is completely unclear how the information about a sustained stimulus is encoded that is perceived for minutes or even longer, when discharge rates have decayed back to spontaneous levels. Using a newly developed statistical approach (multidimensional cluster statistics (MCS)) that allows for a comparison of clusters of data points in n-dimensional space, we here demonstrate that the information about long-lasting stimuli is encoded in the ongoing spatiotemporal activity patterns in sensory cortex. We successfully apply MCS to multichannel local field potential recordings in different rodent models and sensory modalities, as well as to human MEG and EEG data, demonstrating its universal applicability. MCS thus indicates novel ways for the development of powerful read-out algorithms of spatiotemporal brain activity that may be implemented in innovative brain-computer interfaces (BCI).

Two-Photon Bidirectional Control and Imaging of Neuronal Excitability with High Spatial Resolution In Vivo

SummarySensory information is encoded within the brain in distributed spatiotemporal patterns of neuronal activity. Understanding how these patterns influence behavior requires a method to measure and to bidirectionally perturb with high spatial resolution the activity of the multiple neuronal cell types engaged in sensory processing. Here, we combined two-photon holography to stimulate neurons expressing blue light-sensitive opsins (ChR2 and GtACR2) with two-photon imaging of the red-shifted indicator jRCaMP1a in the mouse neocortex in vivo. We demonstrate efficient control of neural excitability across cell types and layers with holographic stimulation and improved spatial resolution by opsin somatic targeting. Moreover, we performed simultaneous two-photon imaging of jRCaMP1a and bidirectional two-photon manipulation of cellular activity with negligible effect of the imaging beam on opsin excitation. This all-optical approach represents a powerful tool to causally dissect how activity patterns in specified ensembles of neurons determine brain function and animal behavior.

A Computationally Efficient Filter for Reducing Shot Noise in Low S/N Data.

Functional multineuron calcium imaging (fMCI) provides a useful experimental platform to simultaneously capture the spatiotemporal patterns of neuronal activity from a large cell population in situ. However, fMCI often suffers from low signal-to-noise ratios (S/N). The main factor that causes the low S/N is shot noise that arises from photon detectors. Here, we propose a new denoising procedure, termed the Okada filter, which is designed to reduce shot noise under low S/N conditions, such as fMCI. The core idea of the Okada filter is to replace the fluorescence intensity value of a given frame time with the average of two values at the preceding and following frames unless the focused value is the median among these three values. This process is iterated serially throughout a time-series vector. In fMCI data of hippocampal neurons, the Okada filter rapidly reduces background noise and significantly improves the S/N. The Okada filter is also applicable for reducing shot noise in electrophysiological data and photographs. Finally, the Okada filter can be described using a single continuous differentiable equation based on the logistic function and is thus mathematically tractable.

Is a multi array-contact lead able to improve STN-DBS in Parkinson’s Disease?

Background Multi-directional electrodes in STN-DBS give the possibility to steer the high frequency current into the direction for clinical improvement and moreover recording of multi-array local field potential recordings (LFPs) give the possibility to determine the spatiotemporal distribution of oscillatory power across the STN that is related to the symptomatology in PD patients. Ultimately this information can be used as a feedback to optimize the stimulation parameters. Methods Eight PD patients were included in the study. After micro-electrode recording (MER), to determine the boundaries of the STN, temporarily a prototype of a new 32-contact DBS lead was inserted during the DBS procedure. Different modes of current steering were employed to improve motor symptoms and patients were scored on beneficial and adverse effects. Prior to and immediately after stimulation the distribution of spectral power was recorded by LFPs and spatiotemporal changes were evaluated with Fourier analysis. Results Thresholds of the effects of spherical stimulation were comparable to thresholds of stimulation through the conventional electrode at the same location in 89% of the cases. In eight of fourteen side effects, steering stimulation current increased the threshold for side effects by ⩾ 1 mA compared to spherical stimulation. The size of the therapeutic window could be widened in patient 6, 7 and 8 by steering stimulation in the posterior, posterior and anterior direction, respectively. LFP recordings prior to stimulation yielded the boundaries of the STN by showing increased spectral power particularly in the 13–40 Hz range. Recordings across all directions showed distinct spatiotemporal patterns of neuronal activity, which were related to the pattern of stimulation and the PD symptoms of the patient. Conclusions With a new DBS lead it is possible to steer stimulation current in STN-DBS such that it leads to a larger therapeutic window than with conventional spherical stimulation. Simultaneous LFP recordings across the entire STN provide spatial information about the location of the STN and its disease-related electrical activity. This may potentially be of benefit in predicting how to steer the current towards the sensorimotor part, while avoiding adverse effects.

Commentary: Cerebellar direct current stimulation enhances on-line motor skill acquisition through an effect on accuracy.

In the past decade, human cortical activity has been shown to be modulated by applying direct low electrical current. The current flowing through the skull and brain between two surface electrodes increases excitability of the cortical tissue under the anode and decreases it under the cathode. This transcranial direct current stimulation (tDCS) improves motor adaptation to environmental change (Galea et al., 2011; Hardwick and Celnik, 2014; Parikh and Cole, 2015) as well as skilled motor learning (Reis et al., 2009; Prichard et al., 2014; Cantarero et al., 2015). The cortical sites that have been shown to impact motor control under tDCS stimulation are the primary motor area (M1; Nitsche et al., 2003) and the cerebellum (Galea et al., 2011). A recent study investigated the effects of cerebellar tDCS (ctDCS) on motor skill learning (Cantarero et al., 2015). Participants attempted to quickly and accurately navigate a cursor on a screen by modulating the isometric key pinch force. To perform the sequential visual isometric pinch task (Reis et al., 2009; Cantarero et al., 2015), the brain has to integrate three types of information: visual feedback, force feedback (proprioception), and motor command. Therefore, improving sensory-motor integration would improve performance in this task. Recently, the cerebellum has shown multimodal arrangements, providing an anatomical basis for this sensory-motor integration. Proville et al. (2014) demonstrated that sensory and motor information from the cerebral cortex converges on single cells in the cerebellum. Proprioceptive information from the spinocerebellar tract and motor information from the cerebral cortex also converge on single cells in the cerebellum (Huang et al., 2013; Requarth et al., 2014). Therefore, cerebellar stimulation can potentially improve sensory-motor integration. Results of Cantarero et al. (2015) showed that anodal ctDCS improved motor accuracy relative to anodal tDCS and sham groups. The improved accuracy was not associated with reduced movement speed (Cantarero et al., 2015, Figure 3C). This change in the speed-accuracy tradeoff demonstrated an improvement in motor skill. Although not reported in the text, Figure 3A in Cantarero et al. (2015) clearly showed that the effect of ctDCS on accuracy was not gradual but immediate (Day 1, Block 2), consistent with the immediate enhancement of conditioned eyeblink responses reported during anodal ctDCS (Zuchowski et al., 2014). After this immediate shift, accuracy remained stable across training days and did not show a typical learning curve. The effect of ctDCS on motor accuracy is unlikely related to the visual system which can hardly be improved. This effect may rather result from improved proprioception. Specifically, in the sequential visual isometric pinch task, improving proprioception would improve the ability to accurately match visual and muscle-force information. Based on studies testing cerebellar patients (e.g., Bhanpuri et al., 2013), it has been suggested that the integration of peripheral proprioceptive information and central motor information in the cerebellum (Huang et al., 2013; Requarth et al., 2014) produces refined proprioception (Boisgontier and Swinnen, 2014). Therefore, if ctDCS improves proprioception this is likely through an improvement of this integration. Sensory-motor integration is performed on three types of information: Space, quantity, and time (Walsh, 2003). Proprioception refers to space (e.g., position of the segments) and quantity (e.g., intensity of the muscle contraction). Wessel et al. (2015) showed that anodal ctDCS does not significantly improve online motor skill learning in a synchronization tapping task, suggesting that anodal ctDCS does not impact the temporal component of sensory-motor integration. M1 tDCS also immediately improves performance in a motor skill task, as demonstrated by Prichard et al. (2014), and visible in Reis et al. (2009). Nevertheless, the immediate effects for ctDCS and M1 tDCS may have different grounds. As described above, immediate ctDCS effects may result from an improved proprioception. Immediate M1 tDCS effects could instead be due to refined spatiotemporal patterns of neuronal activity in M1, which have been associated with improved motor control (Peters et al., 2014). Furthermore, Parikh and Cole (2015) showed that applying M1 tDCS during practice of the Grooved pegboard test improved performance on a grip-lift task, thereby suggesting that this tDCS-induced refinement of neuronal activity in M1 could be transferred between tasks. In conclusion, Cantarero et al. (2015) study showed an immediate ctDCS effect on movement accuracy. Here I propose that this effect is mediated by improved sensory-motor integration in the cerebellum resulting in refined proprioception. This immediate effect has also been reported in motor skill learning studies using M1 tDCS, although the underlying mechanism here may instead be related to the refinement of the spatiotemporal patterns of neuronal activity in M1.

Extreme brain events: Higher-order statistics of brain resting activity and its relation with structural connectivity

The brain exhibits a wide variety of spatiotemporal patterns of neuronal activity recorded using functional magnetic resonance imaging as the so-called blood-oxygenated-level–dependent (BOLD) signal. An active area of work includes efforts to best describe the plethora of these patterns evolving continuously in the brain. Here we explore the third-moment statistics of the brain BOLD signals in the resting state as a proxy to capture extreme BOLD events. We find that the brain signal exhibits typically nonzero skewness, with positive values for cortical regions and negative values for subcortical regions. Furthermore, the combined analysis of structural and functional connectivity demonstrates that relatively more connected regions exhibit activity with high negative skewness. Overall, these results highlight the relevance of recent results emphasizing that the spatiotemporal location of the relatively large-amplitude events in the BOLD time series contains relevant information to reproduce a number of features of the brain dynamics during resting state in health and disease.

Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics.

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain.

Stimulus-Entrained Oscillatory Activity Propagates as Waves from Area 18 to 17 in Cat Visual Cortex

Previous studies in cat visual cortex reported that area 18 can actively drive neurons in area 17 through cortico-cortical projections. However, the dynamics of such cortico-cortical interaction remains unclear. Here we used multielectrode arrays to examine the spatiotemporal pattern of neuronal activity in cat visual cortex across the 17/18 border. We found that full-field contrast reversal gratings evoked oscillatory wave activity propagating from area 18 to 17. The wave direction was independent of the grating orientation, and could not be accounted for by the spatial distribution of receptive field latencies, suggesting that the waves are largely mediated by intrinsic connections in the cortex. Different from the evoked waves, spontaneous waves propagated along both directions across the 17/18 border. Together, our results suggest that visual stimulation may enhance the flow of information from area 18 to 17.

Decoding of spatiotemporal activity of auditory information in the cortex

Animals utilize auditory information for survival and communications of conspecifics. A sequence of sound is analyzed in animals’ brain as elementary components such as notes and syllables. It has been reported that auditory information is represented by spatiotemporal activity of primary auditory cortex [1]. However, how the elementary components of sound are encoded from the spatiotemporal activity of neurons is poorly understood. To address this issue, we present a model of auditory cortex, which performs a hierarchical processing of auditory information. The model consists of three layers of 2-dimensional networks. We show that the aspects of the spatiotemporal activity in the primary cortex are encoded by a combination of feature-detective neurons and then by a dynamical attractor in higher-order cortex. The present study provides a clue for understanding the mechanism of how the information of notes and syllables are constructed from spatiotemporal activity of the primary auditory cortex. We propose a neural network model for hierarchical processing of auditory information, which consists of three networks. The auditory information is encoded with spatiotemporal pattern of neuronal activity in the primary auditory (A1) cortex. The model of A1was made based on the previous model by Taniguch and Yamaguchi [2]. Then the spatiotemporal aspect of the neuronal activity is detected by the feature-detective (FD) neurons in the second layer. These FD neurons integrate the spatiotemporal pattern over a short time period, thereby enabling the second layer to represent the information about notes and about the correlation of notes. The information encoded by the FD neurons is then combined as a linkage of attractors in the feature binding (FB) layer, providing a semantic information such as word.

Model-driven therapeutic treatment of neurological disorders: reshaping brain rhythms with neuromodulation

Electric stimulation has been investigated for several decades to treat, with various degrees of success, a broad spectrum of neurological disorders. Historically, the development of these methods has been largely empirical but has led to a remarkably efficient, yet invasive treatment: deep brain stimulation (DBS). However, the efficiency of DBS is limited by our lack of understanding of the underlying physiological mechanisms and by the complex relationship existing between brain processing and behaviour. Biophysical modelling of brain activity, describing multi-scale spatio-temporal patterns of neuronal activity using a mathematical model and taking into account the physical properties of brain tissue, represents one way to fill this gap. In this review, we illustrate how biophysical modelling is beginning to emerge as a driving force orienting the development of innovative brain stimulation methods that may move DBS forward. We present examples of modelling works that have provided fruitful insights in regards to DBS underlying mechanisms, and others that also suggest potential improvements for this neurosurgical procedure. The reviewed literature emphasizes that biophysical modelling is a valuable tool to assist a rational development of electrical and/or magnetic brain stimulation methods tailored to both the disease and the patient's characteristics.

Intracellular and current source density analysis of pretectal input to the optic tectum of the frog

Electrophysiological examination of the ipsilateral pretectotectal projection has proved that pretectal cells elicit strong suppressive responses to the ipsilateral tectum. However, the neural mechanisms underlying the contralateral pretectotectal prejection are still obscure. The present study aimed to examine the synaptic nature of pretectal nuclei and contralateral tectal cells, and to demonstrate the spatiotemporal pattern of neuronal activity in the 2 main brain structures. Intracellular recording and current source density (CSD) analysis were used to test the complexity of neuronal mechanism of pretectotectal information transfer. The pretectal stimulation elicited only one type of response on the contralateral tectum, the inhibitory postsynaptic potential (IPSP). The majority of contra-induced IPSPs were assumed to be polysynaptically driven. In the CSD analysis, only one sink with short latency was observed in each profile. The ipsilateral projection produced a prominent monosynaptic sink in layer 8 of tectum. Recipient neurons were located in layers 6 and 7 of tectum. The result confirmed former findings from ipsilateral intracellular recordings. These results suggest the following neuronal circuit: afferents from the pretectal nuclei broadly inhibit both tectal neuron, and since no second sink occurs in tectal layers, the pretectotectal excitatory afferents probably do not extend over the whole tectum, but are within limited state. The results of intracellular recording and CSD analysis further provide evidence of how pretectal afferent activity flows within the tectal laminae.

Travelling waves in a model of quasi-active dendrites with active spines

Dendrites, the major components of neurons, have many different types of branching structures and are involved in receiving and integrating thousands of synaptic inputs from other neurons. Dendritic spines with excitable channels can be present in large densities on the dendrites of many cells. The recently proposed Spike-Diffuse-Spike (SDS) model that is described by a system of point hot-spots (with an integrate-and-fire process) embedded throughout a passive tree has been shown to provide a reasonable caricature of a dendritic tree with supra-threshold dynamics. Interestingly, real dendrites equipped with voltage-gated ion channels can exhibit not only supra-threshold responses, but also sub-threshold dynamics. This sub-threshold resonant-like oscillatory behaviour has already been shown to be adequately described by a quasi-active membrane. In this paper we introduce a mathematical model of a branched dendritic tree based upon a generalisation of the SDS model where the active spines are assumed to be distributed along a quasi-active dendritic structure. We demonstrate how solitary and periodic travelling wave solutions can be constructed for both continuous and discrete spine distributions. In both cases the speed of such waves is calculated as a function of system parameters. We also illustrate that the model can be naturally generalised to an arbitrary branched dendritic geometry whilst remaining computationally simple. The spatio-temporal patterns of neuronal activity are shown to be significantly influenced by the properties of the quasi-active membrane. Active (sub- and supra-threshold) properties of dendrites are known to vary considerably among cell types and animal species, and this theoretical framework can be used in studying the combined role of complex dendritic morphologies and active conductances in rich neuronal dynamics.

Synchronization effects using a piecewise linear map-based spiking–bursting neuron model

Models of neurons based on iterative maps allows the simulation of big networks of coupled neurons without loss of biophysical properties such as spiking, bursting or tonic bursting and with an affordable computational effort. These models are built over a phenomenological basis and are mainly implemented by the use of iterative two-dimensional maps that can present neuro-computational properties similar to the usual differential models. A piecewise linear two-dimensional map with one fast and one slow coupled variables is used to model spiking–bursting neural behavior. This map shows oscillations similar to other phenomenological models based on maps that require a higher computational effort. The dynamics of coupled neurons is studied for different coupling strengths and the formation of spatio-temporal patterns of neuronal activity is also explored.

Optical recording of spatiotemporal patterns of cardiorespiratory neuronal activity in the nucleus tractus solitarii network imaged in situ

The pattern and distribution of neuronal activity evoked by sensory input in the nucleus tractus solitarii (NTS) is not well understood. In the present study, we performed optical recordings (MiCAM02 system, Brain Vision Inc) in situ to investigate the spatiotemporal pattern of NTS neuronal activity in response to activation of cardiorespiratory inputs. The dorsal medullary surface was exposed and stained with the voltage-sensitive dye, Di-2-ANEPEQ, at the level of calamus scriptorius. Graded electrical stimulation of the central vagus nerve and the brachial plexus (1 ms pulse, 200 ms duration, 1–10 Hz) at low frequency (<5 Hz) evoked a fast (50–75 ms), transient increase in optical activity that adapted rapidly; whereas, high frequency stimulation (>5 Hz) produced a sustained elevation of fluorescence that recovered following termination of the stimulus. In contrast, activation of peripheral chemoreceptors (NaCN, 0.03%) evoked a prolonged (4–6s) increase in optical activity that was superimposed by phasic changes in fluorescence coupled to the respiratory cycle. Synaptic blockade virtually abolished stimulus evoked fluorescence suggesting that optical signals represented post-synaptic activity. These results suggest that optical imaging is capable of detecting differences in spatiotemporal patterns of neuronal activity in the NTS evoked by distinct populations of cardiorespiratory afferents. This work was funded by NIH HL059167.

Near infrared two-photon excitation cross-sections of voltage-sensitive dyes

Microscopy based on voltage-sensitive dyes has proven effective for revealing spatio-temporal patterns of neuronal activity in vivo and in vitro. Two-photon microscopy using voltage-sensitive dyes offers the possibility of wide-field visualization of membrane potential on sub-cellular length scales, hundreds of microns below the tissue surface. Very little information is available, however, about the utility of voltage-sensitive dyes for two-photon imaging purposes. Here we report on measurements of two-photon fluorescence excitation cross-sections for nine voltage-sensitive dyes in a solvent, octanol, intended to simulate the membrane environment. Ultrashort light pulses from a Ti:sapphire laser were used for excitation from 790 to 960 nm, and fluorescein dye was used as a calibration standard. Overall, dyes RH795, RH421, RH414, di-8-ANEPPS, and di-8-ANEPPDHQ had the largest two-photon excitation cross-sections (∼15 × 10 −50 cm 4 s photon −1) in this wavelength region and are therefore potentially useful for two-photon microscopy. Interestingly, di-8-ANEPPDHQ, a chimera constructed from the potentiometric dyes RH795 and di-8-ANEPPS, exhibited larger cross-sections than either of its constituents.

Developmental changes in the spatio-temporal pattern of respiratory neuron activity in the medulla of late fetal rat

We investigated how the spatio-temporal pattern of respiratory neuron network activity in the ventral medulla changes during the late fetal period of rat. Brainstem-spinal cord preparations isolated from rat fetuses on embryonic days 17–21 (E17–E21) were stained with a voltage-sensitive dye for optical image analysis of neuronal activity of the ventral medulla. The spatio-temporal pattern of respiratory neuron activity in the preparation from E20 to E21 was basically identical to that of neonatal rat; pre-inspiratory activity in a limited region of the rostral ventrolateral medulla, the para-facial region, preceded by several hundred milliseconds the onset of inspiratory activity in the more caudal ventrolateral medulla, the pre-Bötzinger complex level. In contrast, in E17–E18 specimens, pre-inspiratory activity could not be detected in the rostral medulla at the level of the facial nucleus. Neuronal activity appeared to begin at the pre-Bötzinger complex level shortly before onset of the inspiratory burst. Strong activity then developed in the facial nucleus and peaked in the post-inspiratory phase. The transition of these patterns of respiratory activity occurred at E19. We conclude that the changes in the spatio-temporal pattern of neuronal activity reflect developmental changes in the cellular elements underlying rhythm generation in the fetal respiratory neuron network. We suggest that the pre-inspiratory neuron network of the para-facial region in the rostral ventrolateral medulla functions as the rhythm generator after E19/20.