Normalization in mouse primary visual cortex

When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron's response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been best characterized in the visual cortex of macaques and cats. Here we study visually evoked normalization in the visual cortex of awake mice using imaging of calcium indicators in large populations of layer 2/3 (L2/3) V1 excitatory neurons and electrophysiological recordings across layers in V1. Regardless of recording method, mouse visual cortical neurons exhibit normalization to varying degrees. The distributions of normalization strength are similar to those described in cats and macaques, albeit slightly weaker on average.

Dynamic structure of motor cortical neuron coactivity carries behaviorally relevant information

Skillful, voluntary movements are underpinned by computations performed by networks of interconnected neurons in the primary motor cortex (M1). Computations are reflected by patterns of coactivity between neurons. Using pairwise spike time statistics, coactivity can be summarized as a functional network (FN). Here, we show that the structure of FNs constructed from an instructed-delay reach task in nonhuman primates is behaviorally specific: Low-dimensional embedding and graph alignment scores show that FNs constructed from closer target reach directions are also closer in network space. Using short intervals across a trial, we constructed temporal FNs and found that temporal FNs traverse a low-dimensional subspace in a reach-specific trajectory. Alignment scores show that FNs become separable and correspondingly decodable shortly after the Instruction cue. Finally, we observe that reciprocal connections in FNs transiently decrease following the Instruction cue, consistent with the hypothesis that information external to the recorded population temporarily alters the structure of the network at this moment.

Normalization in mouse primary visual cortex

When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron's response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been best characterized in the visual cortex of macaques and cats. Here we study visually evoked normalization in the visual cortex of awake mice using optical imaging of calcium indicators in large populations of layer 2/3 (L2/3) V1 excitatory neurons and electrophysiological recordings across layers in V1. Regardless of recording method, mouse visual cortical neurons exhibit normalization to varying degrees. The distributions of normalization strength are similar to those described in cats and macaques, albeit slightly weaker on average.

Large-Scale Algorithmic Search Identifies Stiff and Sloppy Dimensions in Synaptic Architectures Consistent with Murine Neocortical Wiring

Complex systems can be defined by “sloppy” dimensions, meaning that their behavior is unmodified by large changes to specific parameter combinations, and “stiff” dimensions, whose change results in considerable behavioral modification. In the neocortex, sloppiness in synaptic architectures would be crucial to allow for the maintenance of asynchronous irregular spiking dynamics with low firing rates despite a diversity of inputs, states, and short- and long-term plasticity. Using simulations on neural networks with first-order spiking statistics matched to firing in murine visual cortex while varying connectivity parameters, we determined the stiff and sloppy parameters of synaptic architectures across three classes of input (brief, continuous, and cyclical). Algorithmically generated connectivity parameter values drawn from a large portion of the parameter space reveal that specific combinations of excitatory and inhibitory connectivity are stiff and that all other architectural details are sloppy. Stiff dimensions are consistent across input classes with self-sustaining synaptic architectures following brief input occupying a smaller subspace as compared to the other input classes. Experimentally estimated connectivity probabilities from mouse visual cortex are consistent with the connectivity correlations found and fall in the same region of the parameter space as architectures identified algorithmically. This suggests that simple statistical descriptions of spiking dynamics are a sufficient and parsimonious description of neocortical activity when examining structure-function relationships at the mesoscopic scale. Additionally, coarsegraining cell types does not prevent the generation of accurate, informative, and interpretable models underlying simple spiking activity. This unbiased investigation provides further evidence of the importance of the interrelationship of excitatory and inhibitory connectivity to establish and maintain stable spiking dynamical regimes in the neocortex.

Validating markerless pose estimation with 3D X-ray radiography

To reveal the neurophysiological underpinnings of natural movement, neural recordings must be paired with accurate tracking of limbs and postures. Here, we evaluated the accuracy of DeepLabCut (DLC), a deep learning markerless motion capture approach, by comparing it with a 3D X-ray video radiography system that tracks markers placed under the skin (XROMM). We recorded behavioral data simultaneously with XROMM and RGB video as marmosets foraged and reconstructed 3D kinematics in a common coordinate system. We used the toolkit Anipose to filter and triangulate DLC trajectories of 11 markers on the forelimb and torso and found a low median error (0.228 cm) between the two modalities corresponding to 2.0% of the range of motion. For studies allowing this relatively small error, DLC and similar markerless pose estimation tools enable the study of increasingly naturalistic behaviors in many fields including non-human primate motor control.

Chronic wireless neural population recordings with common marmosets

Marmosets are an increasingly important model system for neuroscience in part due to genetic tractability and enhanced cortical accessibility, due to a lissencephalic neocortex. However, many of the techniques generally employed to record neural activity in primates inhibit the expression of natural behaviors in marmosets precluding neurophysiological insights. To address this challenge, we have developed methods for recording neural population activity in unrestrained marmosets across multiple ethological behaviors, multiple brain states, and over multiple years. Notably, our flexible methodological design allows for replacing electrode arrays and removal of implants providing alternative experimental endpoints. We validate the method by recording sensorimotor cortical population activity in freely moving marmosets across their natural behavioral repertoire and during sleep.

Network Analysis of Murine Cortical Dynamics Implicates Untuned Neurons in Visual Stimulus Coding

Unbiased and dense sampling of large populations of layer 2/3 pyramidal neurons in mouse primary visual cortex (V1) reveals two functional sub-populations: neurons tuned and untuned to drifting gratings. Whether functional interactions between these two groups contribute to the representation of visual stimuli is unclear. To examine these interactions, we summarize the population partial pairwise correlation structure as a directed and weighted graph. We find that tuned and untuned neurons have distinct topological properties, with untuned neurons occupying central positions in functional networks (FNs). Implementation of a decoder that utilizes the topology of these FNs yields accurate decoding of visual stimuli. We further show that decoding performance degrades comparably following manipulations of either tuned or untuned neurons. Our results demonstrate that untuned neurons are an integral component of V1 FNs and suggest that network interactions contain information about the stimulus that is accessible to downstream elements.

A platform for semiautomated voluntary training of common marmosets for behavioral neuroscience

Generally behavioral neuroscience studies of the common marmoset employ adaptations of well-established training methods used with macaque monkeys. However, in many cases these approaches do not readily generalize to marmosets indicating a need for alternatives. Here we present the development of one such alternate: a platform for semiautomated, voluntary in-home cage behavioral training that allows for the study of naturalistic behaviors. We describe the design and production of a modular behavioral training apparatus using CAD software and digital fabrication. We demonstrate that this apparatus permits voluntary behavioral training and data collection throughout the marmoset's waking hours with little experimenter intervention. Furthermore, we demonstrate the use of this apparatus to reconstruct the kinematics of the marmoset's upper limb movement during natural foraging behavior.NEW & NOTEWORTHY The study of marmosets in neuroscience has grown rapidly and presents unique challenges. We address those challenges with an innovative platform for semiautomated, voluntary training that allows marmosets to train throughout their waking hours with minimal experimenter intervention. We describe the use of this platform to capture upper limb kinematics during foraging and to expand the opportunities for behavioral training beyond the limits of traditional training sessions. This flexible platform can easily incorporate other tasks.

Recurrent interactions can explain the variance in single trial responses

To develop a complete description of sensory encoding, it is necessary to account for trial-to-trial variability in cortical neurons. Using a linear model with terms corresponding to the visual stimulus, mouse running speed, and experimentally measured neuronal correlations, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups, in encoding and decoding frameworks, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials.

Ensemble stacking mitigates biases in inference of synaptic connectivity

A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.

Functional triplet motifs underlie accurate predictions of single-trial responses in populations of tuned and untuned V1 neurons

Visual stimuli evoke activity in visual cortical neuronal populations. Neuronal activity can be selectively modulated by particular visual stimulus parameters, such as the direction of a moving bar of light, resulting in well-defined trial averaged tuning properties. However, given any single stimulus parameter, a large number of neurons in visual cortex remain unmodulated, and the role of this untuned population is not well understood. Here, we use two-photon calcium imaging to record, in an unbiased manner, from large populations of layer 2/3 excitatory neurons in mouse primary visual cortex to describe co-varying activity on single trials in neuronal populations consisting of both tuned and untuned neurons. Specifically, we summarize pairwise covariability with an asymmetric partial correlation coefficient, allowing us to analyze the resultant population correlation structure, or functional network, with graph theory. Using the graph neighbors of a neuron, we find that the local population, including both tuned and untuned neurons, are able to predict individual neuron activity on a moment to moment basis, while also recapitulating tuning properties of tuned neurons. Variance explained in total population activity scales with the number of neurons imaged, demonstrating larger sample sizes are required to fully capture local network interactions. We also find that a specific functional triplet motif in the graph results in the best predictions, suggesting a signature of informative correlations in these populations. In summary, we show that unbiased sampling of the local population can explain single trial response variability as well as trial-averaged tuning properties in V1, and the ability to predict responses is tied to the occurrence of a functional triplet motif.

Emergent cortical circuit dynamics contain dense, interwoven ensembles of spike sequences

Temporal codes are theoretically powerful encoding schemes, but their precise form in the neocortex remains unknown in part because of the large number of possible codes and the difficulty in disambiguating informative spikes from statistical noise. A biologically plausible and computationally powerful temporal coding scheme is the Hebbian assembly phase sequence (APS), which predicts reliable propagation of spikes between functionally related assemblies of neurons. Here, we sought to measure the inherent capacity of neocortical networks to produce reliable sequences of spikes, as would be predicted by an APS code. To record microcircuit activity, the scale at which computation is implemented, we used two-photon calcium imaging to densely sample spontaneous activity in murine neocortical networks ex vivo. We show that the population spike histogram is sufficient to produce a spatiotemporal progression of activity across the population. To more comprehensively evaluate the capacity for sequential spiking that cannot be explained by the overall population spiking, we identify statistically significant spike sequences. We found a large repertoire of sequence spikes that collectively comprise the majority of spiking in the circuit. Sequences manifest probabilistically and share neuron membership, resulting in unique ensembles of interwoven sequences characterizing individual spatiotemporal progressions of activity. Distillation of population dynamics into its constituent sequences provides a way to capture trial-to-trial variability and may prove to be a powerful decoding substrate in vivo. Informed by these data, we suggest that the Hebbian APS be reformulated as interwoven sequences with flexible assembly membership due to shared overlapping neurons.NEW & NOTEWORTHY Neocortical computation occurs largely within microcircuits comprised of individual neurons and their connections within small volumes (<500 μm³). We found evidence for a long-postulated temporal code, the Hebbian assembly phase sequence, by identifying repeated and co-occurring sequences of spikes. Variance in population activity across trials was explained in part by the ensemble of active sequences. The presence of interwoven sequences suggests that neuronal assembly structure can be variable and is determined by previous activity.

Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks

Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.

Spontaneous activations follow a common developmental course across primary sensory areas in mouse neocortex

Spontaneous propagation of spiking within the local neocortical circuits of mature primary sensory areas is highly nonrandom, engaging specific sets of interconnected and functionally related neurons. These spontaneous activations promise insight into neocortical structure and function, but their properties in the first 2 wk of perinatal development are incompletely characterized. Previously, we have found that there is a minimal numerical sample, on the order of 400 cells, necessary to fully capture mature neocortical circuit dynamics. Therefore we maximized our numerical sample by using two-photon calcium imaging to observe spontaneous activity in populations of up to 1,062 neurons spanning multiple columns and layers in 52 acute coronal slices of mouse neocortex at each day from postnatal day (PND) 3 to PND 15. Slices contained either primary auditory cortex (A1) or somatosensory barrel field (S1BF), which allowed us to compare sensory modalities with markedly different developmental timelines. Between PND 3 and PND 8, populations in both areas exhibited activations of anatomically compact subgroups on the order of dozens of cells. Between PND 9 and PND 13, the spatiotemporal structure of the activity diversified to include spatially distributed activations encompassing hundreds of cells. Sparse activations covering the entire field of view dominated in slices taken on or after PND 14. These and other findings demonstrate that the developmental progression of spontaneous activations from active local modules in the first postnatal week to sparse, intermingled groups of neurons at the beginning of the third postnatal week generalizes across primary sensory areas, consistent with an intrinsic developmental trajectory independent of sensory input.

Multineuronal activity patterns identify selective synaptic connections under realistic experimental constraints

Structured multineuronal activity patterns within local neocortical circuitry are strongly linked to sensory input, motor output, and behavioral choice. These reliable patterns of pairwise lagged firing are the consequence of connectivity since they are not present in rate-matched but unconnected Poisson nulls. It is important to relate multineuronal patterns to their synaptic underpinnings, but it is unclear how effectively statistical dependencies in spiking between neurons identify causal synaptic connections. To assess the feasibility of mapping function onto structure we used a network model that showed a diversity of multineuronal activity patterns and replicated experimental constraints on data acquisition. Using an iterative Bayesian inference algorithm, we detected a select subset of monosynaptic connections substantially more precisely than correlation-based inference, a common alternative approach. We found that precise inference of synaptic connections improved with increasing numbers of diverse multineuronal activity patterns in contrast to increased observations of a single pattern. Surprisingly, neuronal spiking was most effective and precise at revealing causal synaptic connectivity when the lags considered by the iterative Bayesian algorithm encompassed the timescale of synaptic conductance and integration (∼10 ms), rather than synaptic transmission time (∼2 ms), highlighting the importance of synaptic integration in driving postsynaptic spiking. Last, strong synaptic connections were detected preferentially, underscoring their special importance in cortical computation. Even after simulating experimental constraints, top down approaches to cortical connectivity, from function to structure, identify synaptic connections underlying multineuronal activity. These select connections are closely tied to cortical processing.

Decoding thalamic afferent input using microcircuit spiking activity

A behavioral response appropriate to a sensory stimulus depends on the collective activity of thousands of interconnected neurons. The majority of cortical connections arise from neighboring neurons, and thus understanding the cortical code requires characterizing information representation at the scale of the cortical microcircuit. Using two-photon calcium imaging, we densely sampled the thalamically evoked response of hundreds of neurons spanning multiple layers and columns in thalamocortical slices of mouse somatosensory cortex. We then used a biologically plausible decoder to characterize the representation of two distinct thalamic inputs, at the level of the microcircuit, to reveal those aspects of the activity pattern that are likely relevant to downstream neurons. Our data suggest a sparse code, distributed across lamina, in which a small population of cells carries stimulus-relevant information. Furthermore, we find that, within this subset of neurons, decoder performance improves when noise correlations are taken into account.

Local changes in neocortical circuit dynamics coincide with the spread of seizures to thalamus in a model of epilepsy

During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges.

Analysis of graph invariants in functional neocortical circuitry reveals generalized features common to three areas of sensory cortex

Correlations in local neocortical spiking activity can provide insight into the underlying organization of cortical microcircuitry. However, identifying structure in patterned multi-neuronal spiking remains a daunting task due to the high dimensionality of the activity. Using two-photon imaging, we monitored spontaneous circuit dynamics in large, densely sampled neuronal populations within slices of mouse primary auditory, somatosensory, and visual cortex. Using the lagged correlation of spiking activity between neurons, we generated functional wiring diagrams to gain insight into the underlying neocortical circuitry. By establishing the presence of graph invariants, which are label-independent characteristics common to all circuit topologies, our study revealed organizational features that generalized across functionally distinct cortical regions. Regardless of sensory area, random and -nearest neighbors null graphs failed to capture the structure of experimentally derived functional circuitry. These null models indicated that despite a bias in the data towards spatially proximal functional connections, functional circuit structure is best described by non-random and occasionally distal connections. Eigenvector centrality, which quantifies the importance of a neuron in the temporal flow of circuit activity, was highly related to feedforwardness in all functional circuits. The number of nodes participating in a functional circuit did not scale with the number of neurons imaged regardless of sensory area, indicating that circuit size is not tied to the sampling of neocortex. Local circuit flow comprehensively covered angular space regardless of the spatial scale that we tested, demonstrating that circuitry itself does not bias activity flow toward pia. Finally, analysis revealed that a minimal numerical sample size of neurons was necessary to capture at least 90 percent of functional circuit topology. These data and analyses indicated that functional circuitry exhibited rules of organization which generalized across three areas of sensory neocortex.

Information in the brain is represented and processed by populations of interconnected neurons. However, there is a lack of a clear understanding of the structure and organization of circuit wiring, particularly at the mesoscale which spans multiple columns and layers. In this study, we sought to evaluate whether functional circuit architecture generalizes across the neocortex, testing the existence of a functional analogue to the neocortical microcircuit hypothesis. We analyzed the correlational structure of spontaneous circuit activations in primary auditory, somatosensory, and visual neocortex to generate functional topologies. In these graphs, neurons were represented as nodes, and time-lagged firing between neurons were directed edges. Edge weights reflected how many times the lagged firing occurred and was synonymous to the strength of the functional connection between two neurons. The presence of label-independent features, identified by investigating functional circuit topologies under a graph invariant framework, suggest that functionally distinct areas of the neocortex carry features of a generalized functional cortical circuit. Furthermore, our analyses show that the simultaneous recording of large sections of cortical circuitry is necessary to recognize these features and avoid undersampling errors.

Acetylcholine functionally reorganizes neocortical microcircuits

Sensory information is processed and transmitted through the synaptic structure of local cortical circuits, but it is unclear how modulation of this architecture influences the cortical representation of sensory stimuli. Acetylcholine (ACh) promotes attention and arousal and is thought to increase the signal-to-noise ratio of sensory input in primary sensory cortices. Using high-speed two-photon calcium imaging in a thalamocortical somatosensory slice preparation, we recorded action potential activity of up to 900 neurons simultaneously and compared local cortical circuit activations with and without bath presence of ACh. We found that ACh reduced weak pairwise relationships and excluded neurons that were already unreliable during circuit activity. Using action potential activity from the imaged population, we generated functional wiring diagrams based on the statistical dependencies of activity between neurons. ACh pruned weak functional connections from spontaneous circuit activations and yielded a more modular and hierarchical circuit structure, which biased activity to flow in a more feedforward fashion. Neurons that were active in response to thalamic input had reduced pairwise dependencies overall, but strong correlations were conserved. This coincided with a prolonged period during which neurons showed temporally precise responses to thalamic input. Our results demonstrate that ACh reorganizes functional circuit structure in a manner that may enhance the integration and discriminability of thalamic afferent input within local neocortical circuitry.

Circuit reactivation dynamically regulates synaptic plasticity in neocortex

Circuit reactivations involve a stereotyped sequence of neuronal firing and have been behaviourally linked to memory consolidation. Here we use multiphoton imaging and patch-clamp recording, and observe sparse and stereotyped circuit reactivations that correspond to UP states within active neurons. To evaluate the effect of the circuit on synaptic plasticity, we trigger a single spike-timing-dependent plasticity (STDP) pairing once per circuit reactivation. The pairings reliably fall within a particular epoch of the circuit sequence and result in long-term potentiation. During reactivation, the amplitude of plasticity significantly correlates with the preceding 20-25 ms of membrane depolarization rather than the depolarization at the time of pairing. This circuit-dependent plasticity provides a natural constraint on synaptic potentiation, regulating the inherent instability of STDP in an assembly phase-sequence model. Subthreshold voltage during endogenous circuit reactivations provides a critical informative context for plasticity and facilitates the stable consolidation of a spatiotemporal sequence.

Heuristically optimal path scanning for high-speed multiphoton circuit imaging

Population dynamics of patterned neuronal firing are fundamental to information processing in the brain. Multiphoton microscopy in combination with calcium indicator dyes allows circuit dynamics to be imaged with single-neuron resolution. However, the temporal resolution of fluorescent measures is constrained by the imaging frequency imposed by standard raster scanning techniques. As a result, traditional raster scans limit the ability to detect the relative timing of action potentials in the imaged neuronal population. To maximize the speed of fluorescence measures from large populations of neurons using a standard multiphoton laser scanning microscope (MPLSM) setup, we have developed heuristically optimal path scanning (HOPS). HOPS optimizes the laser travel path length, and thus the temporal resolution of neuronal fluorescent measures, using standard galvanometer scan mirrors. Minimizing the scan path alone is insufficient for prolonged high-speed imaging of neuronal populations. Path stability and the signal-to-noise ratio become increasingly important factors as scan rates increase. HOPS addresses this by characterizing the scan mirror galvanometers to achieve prolonged path stability. In addition, the neuronal dwell time is optimized to sharpen the detection of action potentials while maximizing scan rate. The combination of shortest path calculation and minimization of mirror positioning time allows us to optically monitor a population of neurons in a field of view at high rates with single-spike resolution, ∼ 125 Hz for 50 neurons and ∼ 8.5 Hz for 1,000 neurons. Our approach introduces an accessible method for rapid imaging of large neuronal populations using traditional MPLSMs, facilitating new insights into neuronal circuit dynamics.

Imaging action potentials with calcium indicators

The understanding of neuronal circuits has been, and will continue to be, greatly advanced by the simultaneous imaging of action potentials in neuronal ensembles. This protocol describes "bulk" loading of brain slices with acetoxymethyl (AM) ester calcium indicators in order to monitor action potential activity in large populations of neurons simultaneously. The imaging of calcium influx into neurons provides an indirect, but accurate, measure of action potential generation in individual neurons. Single-cell resolution, and thus the easy identification of every active cell, is the key advantage of the technique.

UP states protect ongoing cortical activity from thalamic inputs

Cortical neurons in vitro and in vivo fluctuate spontaneously between two stable membrane potentials: a depolarized UP state and a hyperpolarized DOWN state. UP states temporally correspond with multineuronal firing sequences which may be important for information processing. To examine how thalamic inputs interact with ongoing cortical UP state activity, we used calcium imaging and targeted whole-cell recordings of activated neurons in thalamocortical slices of mouse somatosensory cortex. Whereas thalamic stimulation during DOWN states generated multineuronal, synchronized UP states, identical stimulation during UP states had no effect on the subthreshold membrane dynamics of the vast majority of cells or on ongoing multineuronal temporal patterns. Both thalamocortical and corticocortical PSPs were significantly reduced and neuronal input resistance was significantly decreased during cortical UP states – mechanistically consistent with UP state insensitivity. Our results demonstrate that cortical dynamics during UP states are insensitive to thalamic inputs.

A visual thalamocortical slice

We describe a thalamocortical slice preparation in which connectivity between the mouse lateral geniculate nucleus (LGN) and primary visual cortex (V1) is preserved. Through DiI injections in fixed brains we traced and created a three-dimensional model of the mouse visual pathways. From this computer model we designed a slice preparation that contains a projection from LGN to V1. We prepared brain slices with these predicted coordinates and demonstrated anatomical LGN-V1 connectivity in these slices after LGN tracer injections. We also revealed functional LGN-V1 connectivity by stimulating LGN electrically and detecting responses in layer 4 of V1 using calcium imaging, field potential recordings and whole-cell recordings. We also identified layer-4 neurons that receive direct thalamocortical input. Finally, we compared cortical activity after LGN stimulation with spontaneous cortical activity and found significant overlap of the spatiotemporal dynamics generated by both types of events.

Internal Dynamics Determine the Cortical Response to Thalamic Stimulation

Although spontaneous activity occurs throughout the neocortex, its relation to the activity produced by external or sensory inputs remains unclear. To address this, we used calcium imaging of mouse thalamocortical slices to reconstruct, with single-cell resolution, the spatiotemporal dynamics of activity of layer 4 in the presence or absence of thalamic stimulation. We found spontaneous neuronal coactivations corresponded to intracellular UP states. Thalamic stimulation of sufficient frequency (>10 Hz) triggered cortical activity, and UP states, indistinguishable from those arising spontaneously. Moreover, neurons were activated in identical and precise spatiotemporal patterns in thalamically triggered and spontaneous events. The similarities between cortical activations indicate that intracortical connectivity plays the dominant role in the cortical response to thalamic inputs. Our data demonstrate that precise spatiotemporal activity patterns can be triggered by thalamic inputs and indicate that the thalamus serves to release intrinsic cortical dynamics.

Activity-independent coregulation of IA and Ih in rhythmically active neurons

The fast transient potassium or A current (IA) plays an important role in determining the activity of central pattern generator neurons. We have previously shown that the shal K+ channel gene encodes IA in neurons of the pyloric network in the spiny lobster. To further study how IA shapes pyloric neuron and network activity, we microinjected RNA for a shal-GFP fusion protein into four identified pyloric neuron types. Neurons expressing shal-GFP had a constant increase in IA amplitude, regardless of cell type. This increase in IA was paralleled by a concomitant increase in the hyperpolarization-activated cation current Ih in all pyloric neurons. Despite significant increases in these currents, only modest changes in cell firing properties were observed. We used models to test two hypotheses to explain this failure to change firing properties. First, this may reflect the mislocalization of the expressed shal protein solely to the somata and initial neurites of injected neurons, rendering it electrically remote from the integrating region in the neuropil. To test this hypothesis, we generated a multicompartment model where increases in IA could be localized to the soma, initial neurite, or neuropil/axon compartments. Although spike activity was somewhat more sensitive to increases in neuropil/axon versus somatic/primary neurite IA, increases in IA limited to the soma and primary neurite still evoked much more dramatic changes than were seen in the shal-GFP-injected neurons. Second, the effect of the increased IA could be compensated by the endogenous increase in Ih. To test this, we modeled the compensatory increases of IA and Ih with a cycling two-cell model. We found that the increase in Ih was sufficient to compensate the effects of increased IA, provided that they increase in a constant ratio, as we observed experimentally in both shal-injected and noninjected neurons. Thus an activity-independent homeostatic mechanism maintains constant neuronal activity in the face of dramatic increases in IA.

The cortex as a central pattern generator

Vertebrate spinal cord and brainstem central pattern generator (CPG) circuits share profound similarities with neocortical circuits. CPGs can produce meaningful functional output in the absence of sensory inputs. Neocortical circuits could be considered analogous to CPGs as they have rich spontaneous dynamics that, similar to CPGs, are powerfully modulated or engaged by sensory inputs, but can also generate output in their absence. We find compelling evidence for this argument at the anatomical, biophysical, developmental, dynamic and pathological levels of analysis. Although it is possible that cortical circuits are particularly plastic types of CPG ('learning CPGs'), we argue that present knowledge about CPGs is likely to foretell the basic principles of the organization and dynamic function of cortical circuits.

KChIP1 and frequenin modify shal-evoked potassium currents in pyloric neurons in the lobster stomatogastric ganglion

The transient potassium current (I(A)) plays an important role in shaping the firing properties of pyloric neurons in the stomatogastric ganglion (STG) of the spiny lobster, Panulirus interruptus. The shal gene encodes I(A) in pyloric neurons. However, when we over-expressed the lobster Shal protein by shal RNA injection into the pyloric dilator (PD) neuron, the increased I(A) had somewhat different properties from the endogenous I(A). The recently cloned K-channel interacting proteins (KChIPs) can modify vertebrate Kv4 channels in cloned cell lines. When we co-expressed hKChIP1 with lobster shal in Xenopus oocytes or lobster PD neurons, they produced A-currents resembling the endogenous I(A) in PD neurons; compared with currents evoked by shal alone, their voltage for half inactivation was depolarized, their kinetics of inactivation were slowed, and their recovery from inactivation was accelerated. We also co-expressed shal in PD neurons with lobster frequenin, which encodes a protein belonging to the same EF-hand family of Ca(2+) sensing proteins as hKChIP. Frequenin also restored most of properties of the shal-evoked currents to those of the endogenous A-currents, but the time course of recovery from inactivation was not corrected. These results suggest that lobster shal proteins normally interact with proteins in the KChIP/frequenin family to produce the transient potassium current in pyloric neurons.

Activity-independent homeostasis in rhythmically active neurons

The shal gene encodes the transient potassium current (I(A)) in neurons of the lobster stomatogastric ganglion. Overexpression of Shal by RNA injection into neurons produces a large increase in I(A), but surprisingly little change in the neuron's firing properties. Accompanying the increase in I(A) is a dramatic and linearly correlated increase in the hyperpolarization-activated inward current (I(h)). The enhanced I(h) electrophysiologically compensates for the enhanced I(A), since pharmacological blockade of I(h) uncovers the physiological effects of the increased I(A). Expression of a nonfunctional mutant Shal also induces a large increase in I(h), demonstrating a novel activity-independent coupling between the Shal protein and I(h) enhancement. Since I(A) and I(h) influence neuronal activity in opposite directions, our results suggest a selective coregulation of these channels as a mechanism for constraining cell activity within appropriate physiological parameters.

Voltage-sensitivity of motoneuron NMDA receptor channels is modulated by serotonin in the neonatal rat spinal cord

Both N-methyl-D-aspartate (NMDA) and serotonin (5-HT) receptors contribute to the generation of rhythmic motor patterns in the rat spinal cord. Co-application of these chemicals is more effective at producing locomotor-like activity than either neurochemical alone. In addition, NMDA application to rat spinal motoneurons, synaptically isolated in tetrodotoxin, induces nonlinear membrane behavior that results in voltage oscillations which can be blocked by 5-HT antagonists. However, the mechanisms underlying NMDA and 5-HT receptor interactions pertinent to motor rhythm production remain to be determined. In the present study, an in vitro neonatal rat spinal cord preparation was used to examine whether NMDA receptor-mediated nonlinear membrane voltage is modulated by 5-HT. Whole-cell recordings of spinal motoneurons demonstrated that 5-HT shifts the region of NMDA receptor-dependent negative slope conductance (RNSC) of the current-voltage relationship to more hyperpolarized potentials and enhances whole-cell inward current. The influence of 5-HT on the RNSC was similar to the effect on the RNSC of decreasing the extracellular Mg(2+)concentration. The results suggest that 5-HT may modulate this form of membrane voltage nonlinearity by regulating Mg(2+) blockade of the NMDA ionophore.

NMDA receptor-mediated oscillatory properties: potential role in rhythm generation in the mammalian spinal cord

Previous studies have demonstrated that (1) NMDA receptor activation occurs during locomotor network operation in lower and higher vertebrates and (2) NMDA induces active membrane properties that can be expressed as intrinsic voltage fluctuations in cells located in the spinal cord of lower vertebrates, as well as in neurons located in supraspinal regions of the mammalian nervous system. This paper reviews recent data showing that NMDA can induce similar inherent membrane potential behavior in synaptically isolated motoneurons and interneurons in the mammalian (in vitro neonatal rat) spinal cord. These TTX-resistant voltage fluctuations include rhythmic oscillations and plateau potentials, as well as low-frequency long-lasting voltage shifts (LLVSs). 5-HT facilitates the transformation of LLVSs into oscillatory events, and 5-HT receptor antagonists have the reverse effect. In the absence of TTX, locomotor-related rhythmic drive potentials in spinal cord neurons can display nonlinear voltage behavior compatible with NMDA receptor activation, although other voltage-activated conductances are not excluded. Suppression of the nonlinear voltage response associated with NMDA receptor activation, via removal of Mg2+, disrupts locomotor patterns of network activity. The potential role of NMDA receptor activation in the operation of mammalian locomotor networks is discussed in the context of these recent observations.

NMDA receptor-mediated oscillatory activity in the neonatal rat spinal cord is serotonin dependent

The effect of serotonin (5-HT) receptor blockade on rhythmic network activity and on N-methyl--aspartate (NMDA) receptor-induced membrane voltage oscillations was examined using an in vitro neonatal rat spinal cord preparation. Pharmacologically induced rhythmic hindlimb activity, monitored via flexor and extensor electroneurograms or ventral root recordings, was abolished by 5-HT receptor antagonists. Intrinsic motoneuronal voltage oscillations, induced by NMDA in the presence of tetrodotoxin (TTX), either were abolished completely or transformed to long-lasting voltage shifts by 5-HT receptor antagonists. Conversely, 5-HT application facilitated the expression of NMDA-receptor-mediated rhythmic voltage oscillations. The results suggest that an interplay between 5-HT and NMDA receptor actions may be critical for the production of rhythmic motor behavior in the mammalian spinal cord, both at the network and single cell level.

NMDA receptor activation triggers voltage oscillations, plateau potentials and bursting in neonatal rat lumbar motoneurons in vitro

Whole-cell recordings of lumbar motoneurons in the intact neonatal rat spinal cord in vitro were undertaken to examine the effects of N-methyl-D-aspartate (NMDA) receptor activation on membrane behaviour. Bath application of NMDA induced rhythmic voltage oscillations of 5.9+/-2.1 mV (SD) at a frequency of 4.4+/-1.5 Hz. Amplitude, but not frequency, of the voltage oscillations was membrane potential-dependent. Voltage oscillations could recruit action potentials and/or plateau potentials with or without superimposed bursting. Blockade of synaptic transmission with tetrodotoxin (TTX) sometimes resulted in a loss of oscillatory activity which could then be restored by increasing the NMDA concentration. After application of TTX, the trajectory of NMDA-induced oscillations was similar to the trajectory induced in the presence of intact synaptic networks, although the mean oscillation duration was longer and the oscillation frequency was slower (1.8+/-1.1 Hz). Current ramps delivered after bath application of NMDA demonstrated bistable membrane properties which may underlie the plateau potentials. Injection of intracellular current pulses could initiate, entrain and terminate individual plateau potentials. The results suggest that membrane depolarization produced by oscillations may activate other intrinsic conductances which generate plateau potentials, thereby providing the neuron with enhanced voltage sensitivity, compared to that produced by NMDA receptor activation alone. These oscillatory events may have a role in the regulation of motor output in a variety of rhythmic behaviours including locomotion.

Lamina VII neurons are rhythmically active during locomotor-like activity in the neonatal rat spinal cord

The midsagittally-sectioned lumbar spinal cord with thoracic segments intact retains the capacity for locomotor-like activity. Intracellular recordings were used to characterize the activity and concurrently label lumbar neurons in lamina VII, an area previously implicated in the generation of locomotion. Sharp electrodes were shown to preferentially impale larger neurons. These neurons undergo rhythmic voltage oscillations, presumably synaptically driven, during locomotor-like activity induced by bath application of N-methyl-D-aspartate and 5-hydroxytryptamine. This supports the hypothesis that synaptic activity recruits neurons in lamina VII that are associated with locomotor behavior.

Long-duration, frequency-dependent motor responses evoked by ventrolateral funiculus stimulation in the neonatal rat spinal cord

Three variations of the in vitro neonatal rat spinal cord preparation were used to investigate motor responses to stimulation of the ventrolateral funiculus (VLF). In a partially hemisected spinal cord preparation, stimuli elicited frequency-dependent activity in lumbar ventral roots that outlasted the stimulus train by up to 30 s. In a spinal cord-hindlimb preparation, trains of VLF stimuli elicited slow, step-like flexor-extensor hindlimb movement that also persisted for up to 30 s beyond the stimulus. Finally, in a partially hemisected spinal cord preparation where 5-hydroxytryptamine/N-methyl-D-aspartate was used to induce locomotor-like rhythmic activity, short trains of VLF stimuli were capable of perturbing the locomotor rhythm, transiently altering its frequency. Application of pharmacological antagonists suggests that these responses may be the result of stimulation of a descending pathway that includes glutamatergic and catecholaminergic fibres comprising part of a descending locomotor command path.

Necrotizing vasculitis in gynecological surgery

Extensive clinical investigation of asymptomatic vasculitis found in routine histopathological studies following gynecological surgery may often be unnecessary. In 11 patients necrotizing angiitis was an incidental finding in surgically removed uterine and uterine adnexal tissues. Following irradiation for urinary bladder carcinoma, one patient died during radical surgery: vasculitis was found in surgically resected pelvic organs, colon and kidneys. In other patients, vasculitis may have been attributable to drugs, e.g. penicillin, or to local arthus-like reaction following cone biopsy of cervix. Available from 6 of these cases, follow-up data presented no evidence of progressive systemic vascular disease, supporting the view that incidentally encountered necrotizing angiitis of uterus and uterine adnexa, like that of the appendix, may be innocuous.