Deriving excitatory neurons of the neocortex from pluripotent stem cells

The human cerebral cortex is an immensely complex structure that subserves critical functions that can be disrupted in developmental and degenerative disorders. Recent innovations in cellular reprogramming and differentiation techniques have provided new ways to study the cellular components of the cerebral cortex. Here, we discuss approaches to generate specific subtypes of excitatory cortical neurons from pluripotent stem cells. We review spatial and temporal aspects of cortical neuron specification that can guide efforts to produce excitatory neuron subtypes with increased resolution. Finally, we discuss distinguishing features of human cortical development and their translational ramifications for cortical stem cell technologies.     

Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition

The temporal features of tactile stimuli are faithfully represented by the activity of neurons in the somatosensory cortex. However, the cellular mechanisms that enable cortical neurons to report accurate temporal information are not known. Here, we show that in the rodent barrel cortex, the temporal window for integration of thalamic inputs is under the control of thalamocortical feed-forward inhibition and can vary from 1 to 10 ms. A single thalamic fiber can trigger feed-forward inhibition and contacts both excitatory and inhibitory cortical neurons. The dynamics of feed-forward inhibition exceed those of each individual synapse in the circuit and are captured by a simple disynaptic model of the thalamocortical projection. The variations in the integration window produce changes in the temporal precision of cortical responses to whisker stimulation. Hence, feed-forward inhibitory circuits, classically known to sharpen spatial contrast of tactile inputs, also increase the temporal resolution in the somatosensory cortex.     

Target and temporal pattern selection at neocortical synapses

We attempt to summarize the properties of cortical synaptic connections and the precision with which they select their targets in the context of information processing in cortical circuits. High-frequency presynaptic bursts result in rapidly depressing responses at most inputs onto spiny cells and onto some interneurons. These 'phasic' connections detect novelty and changes in the firing rate, but report frequency of maintained activity poorly. By contrast, facilitating inputs to interneurons that target dendrites produce little or no response at low frequencies, but a facilitating-augmenting response to maintained firing. The neurons activated, the cells they in turn target and the properties of those synapses determine which parts of the circuit are recruited and in what temporal pattern. Inhibitory interneurons provide both temporal and spatial tuning. The 'forward' flow from layer-4 excitatory neurons to layer 3 and from 3 to 5 activates predominantly pyramids. 'Back' projections, from 3 to 4 and 5 to 3, do not activate excitatory cells, but target interneurons. Despite, therefore, an increasing complexity in the information integrated as it is processed through these layers, there is little 'contamination' by 'back' projections. That layer 6 acts both as a primary input layer feeding excitation 'forward' to excitatory cells in other layers and as a higher-order layer with more integrated response properties feeding inhibition to layer 4 is discussed.     

Synaptic integration fields and associative plasticity of visual cortical cells in vivo

Two major constraints in connectivity decide the spatial extent of visual cortical receptive fields, both during development and adult functioning: 1) feedforward input, extrinsic to visual cortex, is organized in an orderly projection to form a point-to-point mapping of the retina onto the cortical mantle and constitutes the core of the minimal discharge field (MDF) after amplification by local intracortical circuits; and 2) a second type of connectivity consists of long distance horizontal intracortical connections which are thought to favor the binding of local visual operations occurring simultaneously in different parts of the visual field. We review here possible factors, intrinsic to the considered cortical cell, that may control the effectiveness of post-synaptic integration. Their expression during sensory recognition could depend on the spatio-temporal distribution of active inputs onto the target cell dendrite and on their interplay with non-linearities of the membrane properties. On the basis of intracellular recordings in cat area 17, we have observed that peripheral responses (excitatory and inhibitory) could be boosted by coincident postsynaptic depolarization. This effect is lost if the response and the postsynaptic depolarization are mismatched by 1000 ms, suggesting that temporal correlation of central and peripheral responses could regulate in a non-linear manner the gain of center-surround interactions. This temporal selectivity is compatible with up-regulation of composite potentials by the transient voltage-dependent activation of slowly inactivating conductances in visual cortical neurons. A direct consequence of these different considerations is that the receptive field (RF) of neurons in visual pathways should not be considered as a static hardwired window probing the outer environment, but as an active filter which may continuously adapt and be updated as a function of global context and past experience.     

Epileptiform activity in a neocortical network: a mathematical model

 A simple mathematical model describing the generation and propagation of epileptiform activity in a cerebral cortical network is presented. The model consists of a system of nonlinear delay differential equations. Physiological properties are taken into account as nonlinear transmission of signals at the synapse, temporal and spatial summation of incoming signals at the soma, active membrane characteristics, and dendritic and axonal propagation times. The influence of the connectivity and the temporal parameters on the oscillatory properties of the model is studied. The computer simulations are in agreement with experimental observations in cortical networks: whereas a weak excitatory or strong inhibitory synaptic connection strength produces a stationary status with short-lasting responses to external stimuli, increases in excitation or decreases in inhibition induce spontaneous and stimulus-evoked rhythmic discharges. Synaptic burst-like activity is observed only for an intermediate range of excitatory and inhibitory connection strengths and external inputs. The form and duration of the bursts can also be controlled by the temporal parameters. The results demonstrate that relatively simple mathematical equations are sufficient to model some of the network properties underlying the generation and propagation of epileptiform activity. Received: 2 October 2000 / Accepted in revised form: 4 March 2001     

Synaptic integration gradients in single cortical pyramidal cell dendrites

Cortical pyramidal neurons receive thousands of synaptic inputs arriving at different dendritic locations with varying degrees of temporal synchrony. It is not known if different locations along single cortical dendrites integrate excitatory inputs in different ways. Here we have used two-photon glutamate uncaging and compartmental modeling to reveal a gradient of nonlinear synaptic integration in basal and apical oblique dendrites of cortical pyramidal neurons. Excitatory inputs to the proximal dendrite sum linearly and require precise temporal coincidence for effective summation, whereas distal inputs are amplified with high gain and integrated over broader time windows. This allows distal inputs to overcome their electrotonic disadvantage, and become surprisingly more effective than proximal inputs at influencing action potential output. Thus, single dendritic branches can already exhibit nonuniform synaptic integration, with the computational strategy shifting from temporal coding to rate coding along the dendrite.     

Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics

We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This stack can be treated as a multi-input-multi-output system by means of the linear systems theory of homogeneous layers. The detailed equations for the simulation are derived in the Appendix. The results of the simulations show that the temporal and spatial behaviour of an excitation distribution cannot be treated separately. Further, they indicate specific processing in the different layers and some independence from details of wiring. Finally, the simulation results are applied to the theory of visual receptive fields. This yields some insight into the mechanisms possibly underlying hypercomplexity, putative nonlinearities, lateral inhibition, oscillating cell responses, and velocity-dependent tuning curves.     

Synaptic effects elicited in the Retzius cells of the leech Hirudo medicinalis by stimulation of the segmental roots

Electrical stimulation of the segmental roots of each ganglion of Hirudo medicinalis, elicits in both Retzius' cells inhibitory and excitatory effects. The IPSP and EPSP are chemical in nature, being dependent on the membrane potential, and suppressed by high Mg++. Selective inactivation of one RC shows that the responses of the contralateral RC are not due to electrotonic coupling between the two cells, but to synaptic actions impinging upon the membrane of both RCs. The two synaptic potentials appear to be mediated by two set of fibres with a different threshold to electrical stimulation. Their actions on the RCs appear to be polysynaptic on the basis of central latency. Simultaneous stimulation of two roots shows evidence for occlusion for IPSP and summation for EPSP, confirming the polysynaptic nature of the effects. The possible functional significance of the inhibitory and excitatory pathways, is discussed.     

Mesoscopic Patterns of Neural Activity Support Songbird Cortical Sequences

Time-locked sequences of neural activity can be found throughout the vertebrate forebrain in various species and behavioral contexts. From “time cells” in the hippocampus of rodents to cortical activity controlling movement, temporal sequence generation is integral to many forms of learned behavior. However, the mechanisms underlying sequence generation are not well known. Here, we describe a spatial and temporal organization of the songbird premotor cortical microcircuit that supports sparse sequences of neural activity. Multi-channel electrophysiology and calcium imaging reveal that neural activity in premotor cortex is correlated with a length scale of 100 µm. Within this length scale, basal-ganglia–projecting excitatory neurons, on average, fire at a specific phase of a local 30 Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song.     

Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal''s conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations.     

A neuronal network model of primary visual cortex explains spatial frequency selectivity

We address how spatial frequency selectivity arises in Macaque primary visual cortex (V1) by simulating V1 with a large-scale network model consisting of O(10⁴) excitatory and inhibitory integrate-and-fire neurons with realistic synaptic conductances. The new model introduces variability of the widths of subregions in V1 neuron receptive fields. As a consequence different model V1 neurons prefer different spatial frequencies. The model cortex has distributions of spatial frequency selectivity and of preference that resemble experimental findings from the real V1. Two main sources of spatial frequency selectivity in the model are the spatial arrangement of feedforward excitation, and cortical nonlinear suppression, a result of cortical inhibition. Action Editor: Jonathan D. Victor     

Gene regulatory network controlling embryonic specification in the sea urchin

The current state of the gene regulatory network for endomesoderm specification in sea urchin embryos is reviewed. The network was experimentally defined, and is presented as a predictive map of cis-regulatory inputs and functional regulatory gene interconnections (updated versions of the network and most of the underlying data are at ). The network illuminates the 'whys' of many aspects of zygotic control in early sea urchin development, both spatial and temporal. The network includes almost 50 genes, and these are organized in subcircuits, each of which executes a particular regulatory function.     

Differential channeling of sensory stimuli onto a motor neuron in the leech

We studied a specific sensory-motor pathway in the isolated leech ganglia. Pressure-sensitive mechanosensory neurons were stimulated with trains of action potentials at 5–20 Hz while recording the responses of the annulus erector motorneurons that control annuli erection. The response of the annulus erector neurons was a succession of excitatory postsynaptic potentials followed by inhibitory postsynaptic potentials. The excitatory postsynaptic potentials had a brief time-course while the inhibitory postsynaptic potentials had a prolonged time-course that enabled their temporal summation. Thus, the net effect of pressure-sensitive neuron stimulation on the annulus erector neurons was inhibitory. Both phases of the response were mediated by chemical transmission; the excitatory postsynaptic potentials were transmitted via a monosynaptic pathway, and the inhibitory postsynaptic potentials via a polysynaptic one. The pattern of expression of this dual response depended on the field of innervation of the sensory neuron and it was under the influence of cell 151, a non-spiking interneuron, that could regulate the expression of the hyperpolarization. The interaction between pressure-sensitive neurons and annulus erector neuron reveals how sensory specificity, connectivity pattern and regulatory elements interplay in a specific sensory-motor network. Accepted: 6 November 1998     

Neuronal mechanisms of interaction of Deiters nucleus with the cerebral cortex.

The effects of stimulation of the vestibular nerve and five different cerebral cortex areas on the neuronal activity of the lateral vestibular nucleus of Deiters were studied. Stimulation of the cerebral cortex is shown to lead to antidromic and synaptic activation of Deiters neurons. The synaptic potentials of Deiters neurons evoked from the cerebral cortex were of mono- and polysynaptic origin. In particular, stimulation of the cerebral cortex evoked in Deiters neurons mono- and polysynaptic excitatory postsynaptic potentials. Collaterals of vestibulospinal neurons reaching different cortex fields as well as convergence of influences from these cortex fields on Deiters neurons were revealed. Inhibitory effects of the cerebral cortex on Deiters neurons were of polysynaptic origin and occurred rarely. The topical correlation between Deiters nucleus and different areas of the cerebral cortex was found. The peculiarities and functional significance of the effects obtained are discussed.     

Chaos and synchrony in a model of a hypercolumn in visual cortex

Neurons in cortical slices emit spikes or bursts of spikes regularly in response to a suprathreshold current injection. This behavior is in marked contrast to the behavior of cortical neurons in vivo, whose response to electrical or sensory input displays a strong degree of irregularity. Correlation measurements show a significant degree of synchrony in the temporal fluctuations of neuronal activities in cortex. We explore the hypothesis that these phenomena are the result of the synchronized chaos generated by the deterministic dynamics of local cortical networks. A model of a hypercolumn in the visual cortex is studied. It consists of two populations of neurons, one inhibitory and one excitatory. The dynamics of the neurons is based on a Hodgkin-Huxley type model of excitable voltage-clamped cells with several cellular and synaptic conductances. A slow potassium current is included in the dynamics of the excitatory population to reproduce the observed adaptation of the spike trains emitted by these neurons. The pattern of connectivity has a spatial structure which is correlated with the internal organization of hypercolumns in orientation columns. Numerical simulations of the model show that in an appropriate parameter range, the network settles in a synchronous chaotic state, characterized by a strong temporal variability of the neural activity which is correlated across the hypercolumn. Strong inhibitory feedback is essential for the stabilization of this state. These results show that the cooperative dynamics of large neuronal networks are capable of generating variability and synchrony similar to those observed in cortex. Auto-correlation and cross-correlation functions of neuronal spike trains are computed, and their temporal and spatial features are analyzed. In other parameter regimes, the network exhibits two additional states: synchronized oscillations and an asynchronous state. We use our model to study cortical mechanisms for orientation selectivity. It is shown that in a suitable parameter regime, when the input is not oriented, the network has a continuum of states, each representing an inhomogeneous population activity which is peaked at one of the orientation columns. As a result, when a weakly oriented input stimulates the network, it yields a sharp orientation tuning. The properties of the network in this regime, including the appearance of virtual rotations and broad stimulus-dependent cross-correlations, are investigated. The results agree with the predictions of the mean field theory which was previously derived for a simplified model of stochastic, two-state neurons. The relation between the results of the model and experiments in visual cortex are discussed.     

Bayesian inference in populations of cortical neurons: a model of motion integration and segmentation in area MT

A major issue in cortical physiology and computational neuroscience is understanding the interaction between extrinsic signals from feedforward connections and intracortical signals from lateral connections. We propose here a computational model for motion perception based on the assumption that the local cortical circuits in the medio-temporal area (area MT) implement a Bayesian inference principle. This approach establishes a functional balance between feedforward and lateral, excitatory and inhibitory, inputs. The model reproduces most of the known properties of the neurons in area MT in response to moving stimuli. It accounts for important motion perception phenomena including motion transparency, spatial and temporal integration/segmentation. While integrating several properties of previously proposed models, it makes specific testable predictions concerning, in particular, temporal properties of neurons and the architecture of lateral connections in area MT. In addition, the proposed mechanism is consistent with the known properties of local cortical circuits in area V1. This suggests that Bayesian inference may be a general feature of information processing in cortical neuron populations. Received: 3 December 1997 / Accepted in revised form: 21 July 1998     

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons'' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception.     

Spread of excitation in upper layers of the cat auditory cortex with participation of intracortical interneuronal connections

In chronically isolated slabs of the cat auditory cortex with additional transection of lower layers and preservation of the structural integrity of one, two, or three upper layers of cortex just under the pial membrane, impulse responses of slab neurons to stimulation applied at the additionally undercut section were studied. High effectiveness of axodendritic and axospinal excitatory contacts formed by nerve elements of intracortical origin in upper cortical layers was demonstrated. The participation of geniculocortical fibers in spread of excitation in the cortex through synaptic contacts in layer I with dendrites of underlying-layer pyramidal neurons is discussed. The capacity for generation of polysynaptic excitation responses by the neurons indicates preservation of complex interneuronal interactions in the isolated cortex slab preparations with their undercut lower layers.I. I. Mechnikov State University of Odessa, Odessa. Translated from Neirofiziologiya, Vol. 23, No. 1, pp. 80–87, January–February, 1991.