Neuronal firing: does function follow form?

Quantitative analysis of the Golgi impregnated human (neo)striatal neurons: Observation of the morphological characteristics followed by an emphasis on the functional diversity of cells

BACKGROUND

The (neo)striatum is the major input structure of the basal nuclei, which is involved in the execution of voluntary movements, but also in controlling the processes that lead to the movement, such as motivation and cognition. The striatum provides its function through an interaction between projection neurons and interneurons. The aim of this study was to quantify the morphological properties of neurons in the precommissural putamen and precommissural caudate nucleus head and to evaluate whether there is a difference in cell morphology between different cell groups within one part and between the same cell groups within different parts of the striatum.

METHODS

A total of 652 neuronal images of human striatum were observed. The features of the neuronal morphology (soma size, dendritic field size, shape of neuronal image, dendritic curviness, dendritic branching complexity) were observed by determining appropriate parameters of digital images of neurons.

RESULTS

According to the presence of spines on the soma and/or dendrites, neurons were qualitatively classified into 446 spiny and 206 aspiny cells. The analysis of the distribution of the dendritic field area shows that spiny and aspiny neurons from both parts of the neostriatum can be decomposed into two distributions, which means that they can be classified into subgroups. A quantitative analysis of the spiny/aspiny neurons in the human putamen or caudate nucleus head has shown that there is a statistically significant difference between them. By comparing the morphology of neurons of the same group between different parts of the human neostriatum (putamen and caudate nucleus), it was also determined that there is a statistically significant difference.

CONCLUSION

Since the morphology and function of neurons are in close correlation, it can be assumed that different groups of neurons in the human striatum might support functional diversity of the studied area.

Modeling Neurotransmission: Computational Tools to Investigate Neurological Disorders

The investigation of synaptic functions remains one of the most fascinating challenges in the field of neuroscience and a large number of experimental methods have been tuned to dissect the mechanisms taking part in the neurotransmission process. Furthermore, the understanding of the insights of neurological disorders originating from alterations in neurotransmission often requires the development of (i) animal models of pathologies, (ii) invasive tools and (iii) targeted pharmacological approaches. In the last decades, additional tools to explore neurological diseases have been provided to the scientific community. A wide range of computational models in fact have been developed to explore the alterations of the mechanisms involved in neurotransmission following the emergence of neurological pathologies. Here, we review some of the advancements in the development of computational methods employed to investigate neuronal circuits with a particular focus on the application to the most diffuse neurological disorders.

Electrophysiology using coaxial atom probe array: live imaging reveals hidden circuits of a hippocampal neural network

Since the 1960s, it is held that when a neuron fires, a nerve spike passes only through the selective branches, the calculated choice is a key to learning by rewiring. It is argued by chemically estimating the membrane's ion channel density that different axonal branches get active to pass the spike-branches blink at firing at different time domains. Here, using a new time-lapse dielectric imaging, we visualize the classic branch selection process; thenceforth, hidden circuits operating at different time domains become visible. The fractal grid of coaxial probes captures wireless snapshots of material's vibration at various depths below the membrane by setting a suitable frequency. Thus far, branch selection observed emitted energy or particle but never the emitters, what they do. As each dielectric material transmits and reflects signals of different frequencies, we image live how filaments search for many branch-made circuits, choose a unique pathway 10³ times faster than a single nerve spike. It reveals that neural branches and circuit visible in a microscope are not absolute, there coexist many circuits each operating in different dime domains, operating at a time.NEW & NOTEWORTHY Using dielectric resonance scanner, we show electromagnetic field connections between physically separated neurons. Electromagnetic field creates field lines that pass through gap junctions, connect Axon initial segment with the dendrites through Soma, and connect axonal or dendritic branches even if there is no synaptic junction. Consequently, many distinct loops connecting various branches form coexisting circuits. Our discovery suggests that physically appearing neural circuit is a fractional view of many simultaneously operating circuits in different time domains in a neural network.

Cell-Type Specificity of Neuronal Excitability and Morphology in the Central Amygdala

Central amygdala (CeA) neurons expressing protein kinase Cδ (PKCδ⁺) or somatostatin (Som⁺) differentially modulate diverse behaviors. The underlying features supporting cell-type-specific function in the CeA, however, remain unknown. Using whole-cell patch-clamp electrophysiology in acute mouse brain slices and biocytin-based neuronal reconstructions, we demonstrate that neuronal morphology and relative excitability are two distinguishing features between Som⁺ and PKCδ⁺ neurons in the laterocapsular subdivision of the CeA (CeLC). Som⁺ neurons, for example, are more excitable, compact, and with more complex dendritic arborizations than PKCδ⁺ neurons. Cell size, intrinsic membrane properties, and anatomic localization were further shown to correlate with cell-type-specific differences in excitability. Lastly, in the context of neuropathic pain, we show a shift in the excitability equilibrium between PKCδ⁺ and Som⁺ neurons, suggesting that imbalances in the relative output of these cells underlie maladaptive changes in behaviors. Together, our results identify fundamentally important distinguishing features of PKCδ⁺ and Som⁺ cells that support cell-type-specific function in the CeA.

Structural Correlates of CA2 and CA3 Pyramidal Cell Activity in Freely-Moving Mice

Plasticity within hippocampal circuits is essential for memory functions. The hippocampal CA2/CA3 region is thought to be able to rapidly store incoming information by plastic modifications of synaptic weights within its recurrent network. High-frequency spike-bursts are believed to be essential for this process, by serving as triggers for synaptic plasticity. Given the diversity of CA2/CA3 pyramidal neurons, it is currently unknown whether and how burst activity, assessed in vivo during natural behavior, relates to principal cell heterogeneity. To explore this issue, we juxtacellularly recorded the activity of single CA2/CA3 neurons from freely-moving male mice, exploring a familiar environment. In line with previous work, we found that spatial and temporal activity patterns of pyramidal neurons correlated with their topographical position. Morphometric analysis revealed that neurons with a higher proportion of distal dendritic length displayed a higher tendency to fire spike-bursts. We propose that the dendritic architecture of pyramidal neurons might determine burst-firing by setting the relative amount of distal excitatory inputs from the entorhinal cortex.SIGNIFICANCE STATEMENT High-frequency spike-bursts are thought to serve fundamental computational roles within neural circuits. Within hippocampal circuits, spike-bursts are believed to serve as potent instructive signals, which increase the efficiency of information transfer and induce rapid modifications of synaptic efficacies. In the present study, by juxtacellularly recording and labeling single CA2/CA3 neurons in freely-moving mice, we explored whether and how burst propensity relates to pyramidal cell heterogeneity. We provide evidence that, within the CA2/CA3 region, neurons with higher proportion of distal dendritic length display a higher tendency to fire spike-bursts. Thus, the relative amount of entorhinal inputs, arriving onto the distal dendrites, might determine the burst propensity of individual CA2/CA3 neurons in vivo during natural behavior.

Illuminating dendritic function with computational models

Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.

Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.

Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes

In order to further our understanding of how gene expression contributes to key functional properties of neurons, we combined publicly accessible gene expression, electrophysiology, and morphology measurements to identify cross-cell type correlations between these data modalities. Building on our previous work using a similar approach, we distinguished between correlations which were "class-driven," meaning those that could be explained by differences between excitatory and inhibitory cell classes, and those that reflected graded phenotypic differences within classes. Taking cell class identity into account increased the degree to which our results replicated in an independent dataset as well as their correspondence with known modes of ion channel function based on the literature. We also found a smaller set of genes whose relationships to electrophysiological or morphological properties appear to be specific to either excitatory or inhibitory cell types. Next, using data from PatchSeq experiments, allowing simultaneous single-cell characterization of gene expression and electrophysiology, we found that some of the gene-property correlations observed across cell types were further predictive of within-cell type heterogeneity. In summary, we have identified a number of relationships between gene expression, electrophysiology, and morphology that provide testable hypotheses for future studies.

Branching morphology determines signal propagation dynamics in neurons

Computational modeling of signal propagation in neurons is critical to our understanding of basic principles underlying brain organization and activity. Exploring these models is used to address basic neuroscience questions as well as to gain insights for clinical applications. The seminal Hodgkin Huxley model is a common theoretical framework to study brain activity. It was mainly used to investigate the electrochemical and physical properties of neurons. The influence of neuronal structure on activity patterns was explored, however, the rich dynamics observed in neurons with different morphologies is not yet fully understood. Here, we study signal propagation in fundamental building blocks of neuronal branching trees, unbranched and branched axons. We show how these simple axonal elements can code information on spike trains, and how asymmetric responses can emerge in axonal branching points. This asymmetric phenomenon has been observed experimentally but until now lacked theoretical characterization. Together, our results suggest that axonal morphological parameters are instrumental in activity modulation and information coding. The insights gained from this work lay the ground for better understanding the interplay between function and form in real-world complex systems. It may also supply theoretical basis for the development of novel therapeutic approaches to damaged nervous systems.

Universal features of dendrites through centripetal branch ordering

Dendrites form predominantly binary trees that are exquisitely embedded in the networks of the brain. While neuronal computation is known to depend on the morphology of dendrites, their underlying topological blueprint remains unknown. Here, we used a centripetal branch ordering scheme originally developed to describe river networks—the Horton-Strahler order (SO)–to examine hierarchical relationships of branching statistics in reconstructed and model dendritic trees. We report on a number of universal topological relationships with SO that are true for all binary trees and distinguish those from SO-sorted metric measures that appear to be cell type-specific. The latter are therefore potential new candidates for categorising dendritic tree structures. Interestingly, we find a faithful correlation of branch diameters with centripetal branch orders, indicating a possible functional importance of SO for dendritic morphology and growth. Also, simulated local voltage responses to synaptic inputs are strongly correlated with SO. In summary, our study identifies important SO-dependent measures in dendritic morphology that are relevant for neural function while at the same time it describes other relationships that are universal for all dendrites.

Similarly to river beds, dendritic trees of nerve cells form elaborate networks that branch out to cover extensive areas. In the 1940s, ecologist Robert E. Horton developed an ordering system for branches in river networks that was refined in the 1950s by geoscientist Arthur N. Strahler, the Horton-Strahler order (SO). Branches at the tips start with order 1 and increase their order in a systematic way when encountering new branches on the way to the root. SO relationships have recently become popular for quantifying dendritic morphologies. Various branching statistics can be studied as a function of SO. Here we describe that topological measures such as the number of branches, the branch bifurcation ratio and the size of subtrees exhibit stereotypical relations with SO in dendritic trees independently of cell type, mirroring universal features of binary trees. Other functionally more relevant features such as mean branch lengths, local diameters and simulated voltage responses to synaptic inputs directly correlate with SO in a cell type-specific manner, indicating the importance of SO for understanding dendrite growth as well as neural computation.

A cell surface biotinylation assay to reveal membrane-associated neuronal cues: Negr1 regulates dendritic arborization

A complex and still not comprehensively resolved panel of transmembrane proteins regulates the outgrowth and the subsequent morphological and functional development of neuronal processes. In order to gain a more detailed description of these events at the molecular level, we have developed a cell surface biotinylation assay to isolate, detect, and quantify neuronal membrane proteins. When we applied our assay to investigate neuron maturation in vitro, we identified 439 differentially expressed proteins, including 20 members of the immunoglobulin superfamily. Among these candidates, we focused on Negr1, a poorly described cell adhesion molecule. We demonstrated that Negr1 controls the development of neurite arborization in vitro and in vivo. Given the tight correlation existing among synaptic cell adhesion molecules, neuron maturation, and a number of neurological disorders, our assay results are a useful tool that can be used to support the understanding of the molecular bases of physiological and pathological brain function.

In vivo reversible regulation of dendritic patterning by afferent input in bipolar auditory neurons

Afferent input regulates neuronal dendritic patterning locally and globally through distinct mechanisms. To begin to understand these mechanisms, we differentially manipulate afferent input in vivo and assess effects on dendritic patterning of individual neurons in chicken nucleus laminaris (NL). Dendrites of NL neurons segregate into dorsal and ventral domains, receiving excitatory input from the ipsilateral and contralateral ears, respectively, via nucleus magnocellularis (NM). Blocking action potentials from one ear, by either cochlea removal or temporary treatment with tetrodotoxin (TTX), leads to rapid and significant retraction of affected NL dendrites (dorsal ipsilaterally and ventral contralaterally) within 8 h compared with the other dendrites of the same neurons. The degree of retraction is comparable with that induced by direct deafferentation resulting from transection of NM axons. Importantly, when inner ear activity is allowed to recover from TTX treatments, retracted NL dendrites regrow to their normal length within 48 h. The retraction and growth involve elimination of terminal branches and addition of new branches, respectively. Examination of changes in NL dendrites at 96 h after unilateral cochlea removal, a manipulation that induces cell loss in NM and persistent blockage of afferent excitatory action potentials, reveals a significant correlation between cell death in the ipsilateral NM and the degree of dendritic retraction in NL. These results demonstrate that presynaptic action potentials rapidly and reversibly regulate dendritic patterning of postsynaptic neurons in a compartment specific manner, whereas long-term dendritic maintenance may be regulated in a way that is correlated with the presence of silent presynaptic appositions.

Chronic nicotine exposure produces lateralized, age-dependent dendritic remodeling in the rodent basolateral amygdala

This study investigated the dendritic morphology of neurons located in the right and left basolateral amygdala (BLA) and infralimbic (IL) cortex following chronic nicotine exposure during adolescence or adulthood. Sprague-Dawley rats were administered subcutaneous injections of nicotine (0.5 mg/kg; free base) or saline three times per week for 2 weeks (six total injections). The dose period began on either postnatal day (P) 32 (adolescent) or P61 (adult). Twenty days following the end of dosing, brains were processed for Golgi-Cox staining, and dendrites from principal neurons in the BLA and pyramidal neurons in the IL were digitally reconstructed in three dimensions. Morphometric analysis revealed a contrasting pattern of BLA dendritic morphology between the adolescent and adult pretreatment groups. In the adult control group, basilar dendritic length did not differ with respect to hemisphere. Nicotine induced robust hemispheric asymmetry by increasing dendritic length in the right hemisphere only. In contrast, adolescent nicotine exposure did not produce significant alteration of basilar dendritic morphology. There was, however, an indication that nicotine eliminated a naturally existing hemispheric asymmetry in the younger cohort. At both ages, nicotine produced a reduction in complexity of the apical tree of principal neurons. Chronic nicotine did not affect the dendritic morphology of pyramidal neurons from the IL in either age group, indicating another dimension of anatomical specificity. Collectively, these data implicate the BLA as a target for lasting neuroplasticity associated with chronic nicotine exposure. Further, hemispheric differences in dendritic morphology were uncovered that depended on the age of nicotine exposure, a finding that underscores the importance of considering laterality when investigating neurodevelopmental effects of drug exposure.

Tiling among stereotyped dendritic branches in an identified Drosophila motoneuron

Different types of neurons can be distinguished by the specific targeting locations and branching patterns of their dendrites, which form the blueprint for wiring the brain. Unraveling which specific signals control different aspects of dendritic architecture, such as branching and elongation, pruning and cessation of growth, territory formation, tiling, and self-avoidance requires a quantitative comparison in control and genetically manipulated neurons. The highly conserved shapes of individually identified Drosophila neurons make them well suited for the analysis of dendritic architecture principles. However, to date it remains unclear how tightly dendritic architecture principles of identified central neurons are regulated. This study uses quantitative reconstructions of dendritic architecture of an identified Drosophila flight motoneuron (MN5) with a complex dendritic tree, comprising more than 4,000 dendritic branches and 6 mm total length. MN5 contains a fixed number of 23 dendritic subtrees, which tile into distinct, nonoverlapping volumes of the diffuse motor neuropil. Across-animal comparison and quantitative analysis suggest that tiling of the different dendritic subtrees of the same neuron is caused by competitive and repulsive interactions among subtrees, perhaps allowing different dendritic compartments to be connected to different circuit elements. We also show that dendritic architecture is similar among different wildtype and GAL4 driver fly lines. Metric and topological dendritic architecture features are sufficiently constant to allow for studies of the underlying control mechanisms by genetic manipulations. Dendritic territory and certain topological measures, such as tree compactness, are most constant, suggesting that these reflect the intrinsic molecular identity of the neuron. J. Comp. Neurol. 518:2169-2185, 2010. (c) 2010 Wiley-Liss, Inc.

PTX-induced hyperexcitability affects dendritic shape and GABAergic synapse density but not synapse distribution during Manduca postembryonic motoneuron development

During the metamorphosis of the holometabolous insect, Manduca sexta, the postembryonic acquisition of adult specific motor behaviors is accompanied by changes in dendritic architecture, membrane currents, and input synapses of identified motoneurons. This study aims to test whether increased activity affects dendritic architecture and sub-dendritic input synapse distribution of the identified flight motoneuron 5 (MN5). Systemic injections of the chloride channel blocker, picrotoxin (PTX), during early pupal stages increase pupal reflex responsiveness, but overall development is not impaired. MN5 input resistance, resting membrane potential, and spiking threshold are not affected. Bath application of PTX to isolated ventral nerve cords evokes spiking in pupal and adult flight motoneurons. Quantitative three-dimensional reconstructions of the dendritic tree of the adult MN5 show that systemic PTX injections into early pupae cause dendritic overgrowth and reduce the density of GABAergic inputs. In contrast, the distribution patterns of GABAergic terminals throughout the dendritic tree remain unaltered. This indicates that increased overall excitability might cause dendritic overgrowth and decreased inhibitory input during postembryonic motoneuron remodeling, whereas sub-dendritic synapse targeting might be controlled by activity-independent signals. Behavioral testing reveals that these neuronal changes do not impede the animal's ability to fly, but impair maximum flight performance.

Dendrite elongation and dendritic branching are affected separately by different forms of intrinsic motoneuron excitability

Dendrites are the fundamental determinant of neuronal wiring. Consequently dendritic defects are associated with numerous neurological diseases and mental retardation. Neuronal activity can have profound effects on dendritic structure, but the mechanisms controlling distinct aspects of dendritic architecture are not fully understood. We use the Drosophila genetic model system to test the effects of altered intrinsic excitability on postembryonic dendritic architecture development. Targeted dominant negative knock-downs of potassium channel subunits allow for selectively increasing the intrinsic excitability of a selected subset of motoneurons, whereas targeted expression of a genetically modified noninactivating potassium channel decrease intrinsic excitability in vivo. Both manipulations cause significant dendritic overgrowth, but by different mechanisms. Increased excitability causes increased dendritic branch formation, whereas decreased excitability causes increased dendritic branch elongation. Therefore dendritic branching and branch elongation are controlled by separate mechanisms that can be addressed selectively in vivo by different manipulations of neuronal intrinsic excitability.

A two-phase growth strategy in cultured neuronal networks as reflected by the distribution of neurite branching angles

Neurite outgrowth and branching patterns are instrumental in dictating the wiring diagram of developing neuronal networks. We study the self-organization of single cultured neurons into complex networks focusing on factors governing the branching of a neurite into its daughter branches. Neurite branching angles of insect ganglion neurons in vitro were comparatively measured in two neuronal categories: neurons in dense cultures that bifurcated under the presence of extrinsic (cellular environment) cues versus neurons in practical isolation that developed their neurites following predominantly intrinsic cues. Our experimental results were complemented by theoretical modeling and computer simulations. A preferred regime of branching angles was found in isolated neurons. A model based on biophysical constraints predicted a preferred bifurcation angle that was consistent with this range shown by our real neurons. In order to examine the origin of the preferred regime of angles we constructed simulations of neurite outgrowth in a developing network and compared the simulated developing neurons with our experimental results. We tested cost functions for neuronal growth that would be optimized at a specific regime of angles. Our results suggest two phases in the process of neuronal development. In the first, reflected by our isolated neurons, neurons are tuned to make first contact with a target cell as soon as possible, to minimize the time of growth. After contact is made, that is, after neuronal interconnections are formed, a second branching strategy is adopted, favoring higher efficiency in neurite length and volume. The two-phase development theory is discussed in relation to previous results.

Functional connectivity in layer IV local excitatory circuits of rat somatosensory cortex

There are two types of excitatory neurons within layer IV of rat somatosensory cortex: star pyramidal (SP) and spiny stellate cells (SS). We examined the intrinsic properties and connectivity between these neurons to determine differences in function. Eighty-four whole cell recordings of pairs of neurons were examined in slices of rat barrel cortex at 36 +/- 1 degrees C. Only minimal differences in intrinsic properties were found; however, differences in synaptic strength could clearly be shown. Connections between homonymous pairs (SS-SS or SP-SP) had a higher efficacy than heteronymous connections. This difference was mainly a result of quantal content. In 42 pairs, synaptic dynamics were examined. Sequences of action potentials (3-20 Hz) in the presynaptic neuron consistently caused synaptic depression (E2/E1=0.53+/-0.18). The dominant component of depression was release-independent; this depression occurred even when preceding action potentials had failed to cause a response. The release-dependence of depression was target specific; in addition, release-independence was greater for postsynaptic SPs. In a subset of connections formed only between SP and any other cell type (43%), synaptic efficacy was dependent on the presynaptic membrane potential (Vm); at -55 mV, the connections were almost silent, whereas at -85 mV, transmission was very reliable. We suggest that, within layer IV, there is stronger efficacy between homonymous than between heteronymous excitatory connections. Under dynamic conditions, the functional connectivity is shaped by synaptic efficacy at individual connections, by Vm, and by the specificity in the types of synaptic depression.

Heterogeneity of spike frequency adaptation among medium spiny neurones from the rat striatum

The main neuronal population of the striatum is composed of the medium spiny neurones (MSNs). In fact several sub-populations of MSNs can be distinguished according to the striatal compartment (striosomes and matrix) to which they belong, their afferents and their sites of projection, their biochemical markers and their morphologies. However, these cells are generally described as an electrophysiological homogeneous population. Using brain slices from the rat and whole cell patch clamp recordings, we show that at P(15) 28% of the MSNs display a spike frequency adaptation. While the mean frequency adaptation ratio for non-adapting cells was 1.07+/-0.01 it reached 2.66+/-0.09 in adapting MSNs and the incidence of this frequency adaptation phenotype appeared to be stable during post-natal development. Single-cell RT-PCR analysis of mRNAs for mu opioid receptors, enkephalin and substance P precursors suggested that adapting MSNs are present in both striatal compartments as well as in the direct and indirect pathways of the matrix. Adapting neurones were also distinguished from non-adapting cells by a lower membrane time constant, a higher AP threshold, a reduced delay to the first spike and a higher initial firing rate. Micro-domains differing by their magnitude of adaptation could be distinguished within the spike frequency adaptation process.A subgroup of MSNs exists, showing a marked spike frequency adaptation together with other distinct properties, such as shorter delay to first spike and membrane time constant, and higher initial frequency and action potential threshold. In conclusion, when strong cortical inputs are delivered in coincidence, adapting MSNs could not only transmit faster the first AP but also exert a sort of cutoff of the transmission due to their spike frequency adaptation process.

Four cell types with distinctive membrane properties and morphologies in lamina I of the spinal dorsal horn of the adult rat

Lamina I of the spinal dorsal horn plays an important role in the processing and relay of nociceptive information. Signal processing depends, in part, on neuronal membrane properties. Intrinsic membrane properties of lamina I neurons were therefore investigated using whole cell patch clamp recordings in a slice preparation of adult rat spinal cord. Based on responses to somatic current injection, four cell types were identified: tonic, which fire comparatively slowly but continuously throughout stimulation; phasic, which fire a high frequency burst of variable duration; delayed onset, which fire irregularly and with a marked delay to the first spike; and single spike, which typically fire only one action potential even when strongly depolarised. Classification by spiking pattern was further refined by identification of characteristic stimulus-response curves and quantification of several response parameters. Objectivity of the classification was confirmed by cluster analysis. Responses to stimulus trains and synaptic input as well as the kinetics of spontaneous synaptic events revealed differences in the signal processing characteristics of the cell types: tonic and delayed onset cells appeared to act predominantly as integrators whereas phasic and single spike cells acted as coincidence detectors. Intracellular labelling revealed a significant correlation between morphological and physiological cell types: tonic cells were typically fusiform, phasic cells were pyramidal, and delayed onset and single spike cells were multipolar. Thus, there are multiple physiological cells types in lamina I with specific morphological correlates and distinctive signal processing characteristics that confer significant differences in the transduction of input into spike trains.

Evolution and development of time coding systems

Precise temporal coding is a hallmark of both the electrosensory and auditory systems. Selective pressures to improve accuracy or encode more rapid changes have produced a suite of convergent physiological and morphological features that contribute to temporal coding. Comparative studies of temporal coding can also point to shared computational strategies, and suggest how selection might act to improve coding.

Synchronous oscillatory activity in sensory systems: new vistas on mechanisms

The origin and nature, as well as the functional role, of synchronous oscillatory activity in the cortex are among the major unresolved issues in systems neurobiology. Recent advances in understanding the mechanisms underlying oscillations include the description of intrinsically bursting pyramidal cells in striate cortex in vivo and the discovery of inhibitory interneurons that fire spike doublets to induce synchrony. The behavioral consequences of coordinated activity in cortical neurons remain poorly understood.