Plasticity of interneuronal species diversity and parameter variance in neurological diseases

Reduced Synaptic Heterogeneity in a Tetanus Toxin Model of Epilepsy: Insights from Computational Modeling

A neural mass model was used to assess connectivity strength across diverse populations by fitting the model to background EEG data obtained from a Tetanus Toxin rat model of epilepsy. Our findings reveal a notable decline in the variability of estimated parameters when using EEG data recorded from rats in the Tetanus Toxin group compared with the control group. A detailed comparison of standard deviations in estimated parameters between day 1 and day 20 recordings, coinciding with a heightened number of seizures, underscores the impact of Tetanus Toxin on diminishing synaptic strength variability across recordings. This study supports electrophysiological studies suggesting that epileptogenesis induces a reduction in biophysical heterogeneity, potentially leading to an increase in network synchrony associated with epilepsy. Furthermore, our computational model establishes a foundation for future explorations of the implications of this diminished variability.

Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.

Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue

Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".

Synaptic Variability and Cortical Gamma Oscillation Power in Schizophrenia

OBJECTIVE

Cognitive impairments in schizophrenia are associated with lower gamma oscillation power in the prefrontal cortex (PFC). Gamma power depends in part on excitatory drive to fast-spiking parvalbumin interneurons (PVIs). Excitatory drive to cortical neurons varies in strength, which could affect how these neurons regulate network oscillations. The authors investigated whether variability in excitatory synaptic strength across PVIs could contribute to lower prefrontal gamma power in schizophrenia.

METHODS

In postmortem PFC from 20 matched pairs of comparison and schizophrenia subjects, levels of vesicular glutamate transporter 1 (VGlut1) and postsynaptic density 95 (PSD95) proteins were quantified to assess variability in excitatory synaptic strength across PVIs. A computational model network was then used to simulate how variability in excitatory synaptic strength across fast-spiking (a defining feature of PVIs) interneurons (FSIs) regulates gamma power.

RESULTS

The variability of VGlut1 and PSD95 levels at excitatory inputs across PVIs was larger in schizophrenia relative to comparison subjects. This alteration was not influenced by schizophrenia-associated comorbid factors, was not present in monkeys chronically exposed to antipsychotic medications, and was not present in calretinin interneurons. In the model network, variability in excitatory synaptic strength across FSIs regulated gamma power by affecting network synchrony. Finally, greater synaptic variability interacted synergistically with other synaptic alterations in schizophrenia (i.e., fewer excitatory inputs to FSIs and lower inhibitory strength from FSIs) to robustly reduce gamma power.

CONCLUSIONS

The study findings suggest that greater variability in excitatory synaptic strength across PVIs, in combination with other modest synaptic alterations in these neurons, can markedly lower PFC gamma power in schizophrenia.

Integrating single-cell transcriptomics and microcircuit computer modeling

Biophysically realistic computer modeling of neuronal microcircuitry has served as a testing ground for hypotheses related to the structure and function of different brain microcircuits. Recent advances in single-cell transcriptomics provide snapshots of a neuron's molecular state and have demonstrated that cell-specific genetic markers engineer the electrophysiological properties of a neuron. Integrating these molecular details with biophysical modeling can allow unprecedented mechanistic insights. In this opinion review, we consider systems biology-based strategies involving statistical deconvolution and gene ontology to integrate the two approaches. We foresee that this integration will infer the nonlinear interactions between the transcriptomically detailed neurons in different brain states. For an initial assessment of these integrative strategies, we recommend testing them on a penetrant phenotype such as epilepsy or a basic organism model such as Caenorhabditis elegans.

A Tisket a Tasket: Chandelier ≠ Basket (Cell Bouton Density in Sclerotic DG)

GABA bouton subpopulations in the human dentate gyrus are differentially altered in mesial temporal lobe epilepsy Alhourani A, Fish KN, Wozny TA, Sudhakar V, Hamilton RL, Richardson RM. J Neuro . 2020;123(4):392-406. doi:10.1152/jn.00523.2018 Medically intractable temporal lobe epilepsy is a devastating disease, for which surgical removal of the seizure-onset zone is the only known cure. Multiple studies have found evidence of abnormal dentate gyrus network circuitry in human mesial temporal lobe epilepsy (MTLE). Principal neurons within the dentate gyrus gate entorhinal input into the hippocampus provide a critical step in information processing. Crucial to that role are GABA-expressing neurons, particularly parvalbumin (PV)-expressing basket cells (PVBCs) and chandelier cells (PVChCs), which provide strong, temporally coordinated inhibitory signals. Alterations in PVBC and PVChC boutons have been described in epilepsy, but the value of these studies has been limited due to methodological hurdles associated with studying human tissue. We developed a multilabel immunofluorescence confocal microscopy and a custom segmentation algorithm to quantitatively assess PVBC and PVChC bouton densities and to infer relative synaptic protein content in the human dentate gyrus. Using en bloc specimens from MTLE subjects with and without hippocampal sclerosis, paired with nonepileptic controls, we demonstrate the utility of this approach for detecting cell-type specific synaptic alterations. Specifically, we found increased density of PVBC boutons, while PVChC boutons decreased significantly in the dentate granule cell layer of subjects with hippocampal sclerosis compared with matched controls. In contrast, bouton densities for either PV-positive cell type did not differ between epileptic subjects without sclerosis and matched controls. These results may explain conflicting findings from previous studies that have reported both preserved and decreased PV bouton densities and establish a new standard for quantitative assessment of interneuron boutons in epilepsy.

Stationary-State Statistics of a Binary Neural Network Model with Quenched Disorder

In this paper, we study the statistical properties of the stationary firing-rate states of a neural network model with quenched disorder. The model has arbitrary size, discrete-time evolution equations and binary firing rates, while the topology and the strength of the synaptic connections are randomly generated from known, generally arbitrary, probability distributions. We derived semi-analytical expressions of the occurrence probability of the stationary states and the mean multistability diagram of the model, in terms of the distribution of the synaptic connections and of the external stimuli to the network. Our calculations rely on the probability distribution of the bifurcation points of the stationary states with respect to the external stimuli, calculated in terms of the permanent of special matrices using extreme value theory. While our semi-analytical expressions are exact for any size of the network and for any distribution of the synaptic connections, we focus our study on networks made of several populations, that we term "statistically homogeneous" to indicate that the probability distribution of their connections depends only on the pre- and post-synaptic population indexes, and not on the individual synaptic pair indexes. In this specific case, we calculated analytically the permanent, obtaining a compact formula that outperforms of several orders of magnitude the Balasubramanian-Bax-Franklin-Glynn algorithm. To conclude, by applying the Fisher-Tippett-Gnedenko theorem, we derived asymptotic expressions of the stationary-state statistics of multi-population networks in the large-network-size limit, in terms of the Gumbel (double exponential) distribution. We also provide a Python implementation of our formulas and some examples of the results generated by the code.

Ionic Current Variability and Functional Stability in the Nervous System

Identified neurons in different animals express ionic currents at highly variable levels (population variability). If neuronal identity is associated with stereotypical function, as is the case in genetically identical neurons or in unambiguously identified individual neurons, this variability poses a conundrum: How is activity the same if the components that generate it-ionic current levels-are different? In some cases, ionic current variability across similar neurons generates an output gradient. However, many neurons produce very similar output activity, despite substantial variability in ionic conductances. It appears that, in many such cells, conductance levels of one ionic current vary in proportion to the conductance levels of another current. As a result, in a population of neurons, these conductances appear to be correlated. Here, I review theoretical and experimental work that suggests that neuronal ionic current correlation can reduce the global ionic current variability and can contribute to functional stability.

GABAergic synapses: their plasticity and role in sensory cortex

The mammalian neocortex is composed of a variety of cell types organized in a highly interconnected circuit. GABAergic neurons account for only about 20% of cortical neurons. However, they show widespread connectivity and a high degree of diversity in morphology, location, electrophysiological properties and gene expression. In addition, distinct populations of inhibitory neurons have different sensory response properties, capacities for plasticity and sensitivities to changes in sensory experience. In this review we summarize experimental evidence regarding the properties of GABAergic neurons in primary sensory cortex. We will discuss how distinct GABAergic neurons and different forms of GABAergic inhibitory plasticity may contribute to shaping sensory cortical circuit activity and function.

Synchronization in random balanced networks

Characterizing the influence of network properties on the global emerging behavior of interacting elements constitutes a central question in many areas, from physical to social sciences. In this article we study a primary model of disordered neuronal networks with excitatory-inhibitory structure and balance constraints. We show how the interplay between structure and disorder in the connectivity leads to a universal transition from trivial to synchronized stationary or periodic states. This transition cannot be explained only through the analysis of the spectral density of the connectivity matrix. We provide a low-dimensional approximation that shows the role of both the structure and disorder in the dynamics.

Topological and dynamical complexity of random neural networks

Random neural networks are dynamical descriptions of randomly interconnected neural units. These show a phase transition to chaos as a disorder parameter is increased. The microscopic mechanisms underlying this phase transition are unknown and, similar to spin glasses, shall be fundamentally related to the behavior of the system. In this Letter, we investigate the explosion of complexity arising near that phase transition. We show that the mean number of equilibria undergoes a sharp transition from one equilibrium to a very large number scaling exponentially with the dimension on the system. Near criticality, we compute the exponential rate of divergence, called topological complexity. Strikingly, we show that it behaves exactly as the maximal Lyapunov exponent, a classical measure of dynamical complexity. This relationship unravels a microscopic mechanism leading to chaos which we further demonstrate on a simpler disordered system, suggesting a deep and underexplored link between topological and dynamical complexity.

Cell-type specific inactivation of hippocampal CA1 disrupts location-dependent object recognition in the mouse

The allatostatin receptor (AlstR)/ligand inactivation system enables potent regulation of neuronal circuit activity. To examine how different cell types participate in memory formation, we have used this system through Cre-directed, cell-type specific expression in mouse hippocampal CA1 in vivo and examined functional effects of inactivation of excitatory vs. inhibitory neurons on memory formation. We chose to use a hippocampus-dependent behavioral task involving location-dependent object recognition (LOR). The double transgenic mice, with the AlstRs selectively expressed in excitatory pyramidal neurons or inhibitory interneurons, were cannulated, targeting dorsal hippocampus to allow the infusion of the receptor ligand (the allatostatin [AL] peptide) in a time dependent manner. Compared to control animals, AL-infused animals showed no long-term memory for object location. While inactivation of excitatory or inhibitory neurons produced opposite effects on hippocampal circuit activity in vitro, the effects in vivo were similar. Both types of inactivation experiments resulted in mice exhibiting no long-term memory for object location. Together, these results demonstrate that the Cre-directed, AlstR-based system is a powerful tool for cell-type specific manipulations in a behaving animal and suggest that activity of either excitatory neurons or inhibitory interneurons is essential for proper long-term object location memory formation.

Seizures as imbalanced up states: excitatory and inhibitory conductances during seizure-like events

Precisely timed and dynamically balanced excitatory (E) and inhibitory (I) conductances underlie the basis of neural network activity. Normal E/I balance is often shifted in epilepsy, resulting in neuronal network hyperexcitability and recurrent seizures. However, dynamics of the actual excitatory and inhibitory synaptic conductances (ge and gi, respectively) during seizures remain unknown. To study the dynamics of E and I network balance, we calculated ge and gi during the initiation, body, and termination of seizure-like events (SLEs) in the rat hippocampus in vitro. Repetitive emergent SLEs in 4-aminopyridine (100 μM) and reduced extracellular magnesium (0.6 mM) were recorded in the identified CA1 pyramidal cells (PC) and oriens-lacunosum moleculare (O-LM) interneurons. Calculated ge/gi ratio dynamics showed that the initiation stage of the SLEs was dominated by inhibition in the PCs and was more balanced in the O-LM cells. During the body of the SLEs, the balance shifted toward excitation, with ge and gi peaking in both cell types at nearly the same time. In the termination phase, PCs were again dominated by inhibition, whereas O-LM cells experienced persistent excitatory synaptic barrage. In this way, increased excitability of interneurons may play roles in both seizure initiation (žiburkus J, Cressman JR, Barreto E, Schiff SJ. J Neurophysiol 95: 3948-3954, 2006) and in their termination. Overall, SLE stages can be characterized in PC and O-LM cells by dynamically distinct changes in the balance of ge and gi, where a temporal sequence of imbalance shifts with the changing firing patterns of the cellular subtypes comprising the hyperexcitable microcircuits.

New dimensions of interneuronal specialization unmasked by principal cell heterogeneity

Although the diversity of neocortical and hippocampal GABAergic interneurons is recognized in terms of their anatomical, molecular and functional properties, principal cells are usually assumed to constitute homogenous populations. However, even within a single layer, subpopulations of principal cells can often be differentiated by their distinct long-range projection targets. Such subpopulations of principal cells can have different local connection properties and excitatory inputs, forming subnetworks that may serve as separate information-processing channels. Interestingly, as reviewed here, recent evidence has revealed specific instances where interneuron cell types selectively innervated distinct subpopulations of principal cells, targeting only those with particular long-distance projection targets. This organization represents a novel form of interneuron specialization, providing interneurons with the potential to selectively regulate specific information-processing streams.

Cell type-specific long-term plasticity at glutamatergic synapses onto hippocampal interneurons expressing either parvalbumin or CB1 cannabinoid receptor

Different GABAergic interneuron types have specific roles in hippocampal function, and anatomical as well as physiological features vary greatly between interneuron classes. Long-term plasticity of interneurons has mostly been studied in unidentified GABAergic cells and is known to be very heterogeneous. Here we tested whether cell type-specific plasticity properties in distinct GABAergic interneuron types might underlie this heterogeneity. We show that long-term potentiation (LTP) and depression (LTD), two common forms of synaptic plasticity, are expressed in a highly cell type-specific manner at glutamatergic synapses onto hippocampal GABAergic neurons. Both LTP and LTD are generated in interneurons expressing parvalbumin (PV+), whereas interneurons with similar axon distributions but expressing cannabinoid receptor-1 show no lasting plasticity in response to the same protocol. In addition, LTP or LTD occurs in PV+ interneurons with different efferent target domains. Perisomatic-targeting PV+ basket and axo-axonic interneurons express LTP, whereas glutamatergic synapses onto PV+ bistratified cells display LTD. Both LTP and LTD are pathway specific, independent of NMDA receptors, and occur at synapses with calcium-permeable (CP) AMPA receptors. Plasticity in interneurons with CP-AMPA receptors strongly modulates disynaptic GABAergic transmission onto CA1 pyramidal cells. We propose that long-term plasticity adjusts the synaptic strength between pyramidal cells and interneurons in a cell type-specific manner and, in the defined CA1 interneurons, shifts the spatial pattern of inhibitory weight from pyramidal cell dendrites to the perisomatic region.

The functional consequences of cortical circuit abnormalities on gamma oscillations in schizophrenia: insights from computational modeling

Schizophrenia is characterized by cortical circuit abnormalities, which might be reflected in γ-frequency (30–100 Hz) oscillations in the electroencephalogram. Here we used a computational model of cortical circuitry to examine the effects that neural circuit abnormalities might have on γ generation and network excitability. The model network consisted of 1000 leaky integrate-and-fire neurons with realistic connectivity patterns and proportions of neuron types [pyramidal cells (PCs), regular-spiking inhibitory interneurons, and fast-spiking interneurons (FSIs)]. The network produced a γ oscillation when driven by noise input. We simulated reductions in: (1) recurrent excitatory inputs to PCs; (2) both excitatory and inhibitory inputs to PCs; (3) all possible connections between cells; (4) reduced inhibitory output from FSIs; and (5) reduced NMDA input to FSIs. Reducing all types of synaptic connectivity sharply reduced γ power and phase synchrony. Network excitability was reduced when recurrent excitatory connections were deleted, but the network showed disinhibition effects when inhibitory connections were deleted. Reducing FSI output impaired γ generation to a lesser degree than reducing synaptic connectivity, and increased network excitability. Reducing FSI NMDA input also increased network excitability, but increased γ power. The results of this study suggest that a multimodal approach, combining non-invasive neurophysiological and structural measures, might be able to distinguish between different neural circuit abnormalities in schizophrenia patients. Computational modeling may help to bridge the gaps between post-mortem studies, animal models, and experimental data in humans, and facilitate the development of new therapies for schizophrenia and neuropsychiatric disorders in general.

Deletion of the citron kinase gene selectively affects the number and distribution of interneurons in barrelfield cortex

Citron kinase (CIT-K), a ser/thr kinase, is required during neurogenesis for cytokinesis of neuronal precursors. Deletion of the cit-k gene in mice (cit-k(-/-) mice) leads to a severe malformative central nervous system syndrome characterized by microencephaly, ataxia, and epileptic seizures; affected mice die by the third week of postnatal life. We have used NADPH-diaphorase histochemistry, immunostaining for calbindin, calretinin, parvalbumin, and glutamic acid decarboxylase 67 (GAD67), and histological staining to undertake qualitative and quantitative analyses of the morphology and distribution of interneurons in the barrelfield cortex of cit-k(-/-) mice. By postnatal day 13, lack of CIT-K results in profoundly altered cortical cell morphology: the infragranular layers are populated by large, binucleate interneurons bearing many more dendrites than in control mice, an anatomical profile that has also been reported for the cortex of humans with cortical dysplasias and epilepsy. Tessellation analyses reveal that a clustered distribution of interneurons is maintained in cit-k(-/-) mice, but that their nearest neighbor distance is significantly increased, and thus their density is reduced; the overall number of interneurons is more dramatically decreased in the absence of CIT-K than would be predicted on the basis of the reduced brain size of affected mice. This reduction of inhibitory gamma-aminobutyric acid (GABA)ergic neurons likely underlies the occurrence of epileptic seizures in the cit-k(-/-) mice. Furthermore, the altered distribution of NADPH-diaphorase-positive interneurons could be responsible for an impaired coupling of cortical activity to blood flow, also affecting cortical growth and functioning.

Suicide and depression in the quantitative analysis of glutamic acid decarboxylase-Immunoreactive neuropil

BACKGROUND

Alterations of GABAergic neurotransmission are assumed to play a crucial role in the pathophysiology of mood disorders. Glutamic acid decarboxylase (GAD) is the key enzyme of GABA synthesis.

METHODS

Immunohistochemical staining of GAD 65/67 was performed in the orbitofrontal, anterior cingulate and dorsolateral prefrontal cortex (DLC), the entorhinal cortex (EC), the hippocampal formation, and the medial dorsal and lateral dorsal thalamic nuclei, with consecutive determination of GAD-immunoreactive (-ir) neuropil relative density. The study was performed on paraffin-embedded brains from 21 depressed patients (14 of whom had committed suicide) and 18 matched controls. The data were tested using Kruskal-Wallis, Mann-Whitney (U) and Spearman statistical procedures.

RESULTS

As shown by post-hoc U-tests, an increase in the relative density of GAD-ir neuropil was present in the hippocampal formation, specific for suicidal patients. The EC was the only area where non-suicidal patients also revealed an increase compared with controls. On the contrary, the DLC was the only area where a significant decrease existed, specific for non-suicidal patients. Numerous negative correlations were found between the investigated parameter and psychotropic medication.

LIMITATIONS

A major limitation of this study is the relatively small case number. A further limitation is given by the lack of data on drug exposure across the whole life span. The possible impact of unipolar-bipolar dichotomy of mood disorders on the obtained results should also be considered.

CONCLUSION

The study, revealing predominantly an increased relative density of GAD-ir neuropil, suggests the diathesis of GABAergic system specific for depressed suicidal patients.

Mouse chromosome 11 harbors genetic determinants of hippocampal strain-specific nicotinic receptor expression

Differences between isogenic mouse strains in cellular expression of the neuronal nicotinic acetylcholine (ACh) receptor subunit alpha 4 (nAChR alpha 4) by the dorsal hippocampus are well known. To investigate further the genetic basis of these variations, expression of the nAChR alpha 4 subunit was measured in congenic mouse lines derived from two strains exhibiting notable divergence in the expression of this subunit: C3H and C57BL/6. Congenic lines carrying reciprocally introgressed regions (quantitative trait loci; QTL) from chromosomes 4, 5, and 12 each retained the phenotype most closely associated with the parental strain. However, in congenic lines harboring the reciprocal transfer of a chromosome 11 QTL, a characteristic difference in the ratio of interneurons versus astrocytes expressing nAChR alpha 4 in the CA1 region is reversed relative to the parental strain. These finding suggest that this chromosomal segment harbors genes that regulate strain distinct hippocampal morphology that is revealed by nAChR alpha 4 expression.

Spontaneous plasticity of multineuronal activity patterns in activated hippocampal networks

Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

Progressive synaptic pathology of motor cortical neurons in a BAC transgenic mouse model of Huntington's disease

Huntington's disease (HD) is a neurodegenerative disorder caused by a polyglutamine repeat expansion in huntingtin. A newly developed bacterial artificial chromosome transgenic mouse model (BACHD) reproduces phenotypic features of HD including predominantly neuropil-associated protein aggregation and progressive motor dysfunction with selective neurodegenerative pathology. Motor dysfunction has been shown to precede neuropathology in BACHD mice. We therefore investigated the progression of synaptic pathology in pyramidal cells and interneurons of the superficial motor cortex of BACHD mice. Whole-cell patch clamp recordings were performed on layer 2/3 primary motor cortical pyramidal cells and parvalbumin interneurons from BACHD mice at 3 months, when the mice begin to demonstrate mild motor dysfunction, and at 6 months, when the motor dysfunction is more severe. Changes in synaptic variances were detectable at 3 months, and at 6 months BACHD mice display progressive synaptic pathology in the form of reduced cortical excitation and loss of inhibition onto pyramidal cells. These results suggest that progressive alterations of the superficial cortical circuitry may contribute to the decline of motor function in BACHD mice. The synaptic pathology occurs prior to neuronal degeneration and may therefore prove useful as a target for future therapeutic design.

Retardation in somatosensory cortex development induced by postnatal BrdU treatment in mice

Cerebral dysgeneses are in the background of several neurological and mental disturbances. The aim of the present study was to investigate structural and activity changes following disturbed postnatal neuronal development in mice. Newborn C57Bl6 mice were exposed to 5-bromo-2'-deoxyuridine (BrdU: daily 50 microg/g body weight) during a period between postnatal days P0-P5 or P0-P11, respectively, and neuronal malformation and malfunctioning of somatosensory (barrel field) cortex was analyzed in adolescent animals. Alterations in histological architecture of interneuronal and glial elements were studied and correlated with electrophysiological modifications. Between P30 and P35 days litters underwent ex vivo electrophysiological experiments to examine the changes in basic excitability and in synaptic efficacy. Parallel immunohistochemistry was performed to detect BrdU, GABA and GFAP. There were no BrdU immunopositive cell nuclei in control animals, but marked staining was observed in both BrdU treated groups. Lessening in the number of GABAergic neurons was observed in the treated groups. GFAP immunohistochemical analysis has shown an increased number of activated astroglial cells in treated animals. Reduction of the number of GABAergic neurons was observed in the treated groups. Electrophysiological recordings on cortical slices showed increased excitability in the treated groups.

Homeostatic plasticity studied using in vivo hippocampal activity-blockade: synaptic scaling, intrinsic plasticity and age-dependence

Homeostatic plasticity is thought to be important in preventing neuronal circuits from becoming hyper- or hypoactive. However, there is little information concerning homeostatic mechanisms following in vivo manipulations of activity levels. We investigated synaptic scaling and intrinsic plasticity in CA1 pyramidal cells following 2 days of activity-blockade in vivo in adult (postnatal day 30; P30) and juvenile (P15) rats. Chronic activity-blockade in vivo was achieved using the sustained release of the sodium channel blocker tetrodotoxin (TTX) from the plastic polymer Elvax 40W implanted directly above the hippocampus, followed by electrophysiological assessment in slices in vitro. Three sets of results were in general agreement with previous studies on homeostatic responses to in vitro manipulations of activity. First, Schaffer collateral stimulation-evoked field responses were enhanced after 2 days of in vivo TTX application. Second, miniature excitatory postsynaptic current (mEPSC) amplitudes were potentiated. However, the increase in mEPSC amplitudes occurred only in juveniles, and not in adults, indicating age-dependent effects. Third, intrinsic neuronal excitability increased. In contrast, three sets of results sharply differed from previous reports on homeostatic responses to in vitro manipulations of activity. First, miniature inhibitory postsynaptic current (mIPSC) amplitudes were invariably enhanced. Second, multiplicative scaling of mEPSC and mIPSC amplitudes was absent. Third, the frequencies of adult and juvenile mEPSCs and adult mIPSCs were increased, indicating presynaptic alterations. These results provide new insights into in vivo homeostatic plasticity mechanisms with relevance to memory storage, activity-dependent development and neurological diseases.

Modulation of Cellular and Synaptic Variability in the Lamprey Spinal Cord

Variability is increasingly recognized as a characteristic feature of cellular, synaptic, and network properties. While studies have traditionally focused on mean values, significant effects can result from changes in variance. This study has examined cellular and synaptic variability in the lamprey spinal cord and its modulation by the neuropeptide substance P. Cellular and synaptic variability differed in different types of cell and synapse. Substance P reduced the variability of subthreshold locomotor-related depolarizations and spiking in motor neurons during network activity. These effects were associated with a reduction in the variability of spiking in glutamatergic excitatory network interneurons and with a reduction in the variance of excitatory interneuron-evoked excitatory postsynaptic potentials (EPSPs). Substance P also reduced the variance of postsynpatic potentials (PSPs) from crossing inhibitory and excitatory interneurons, but it increased the variance of inhibitory postsynpatic potentials (IPSPs) from ipsilateral inhibitory interneurons. The effects on the variance of different PSPs could occur with or without changes in the PSP amplitude. The reduction in the variance of excitatory interneuron-evoked EPSPs was protein kinase A, calcium, and N-methyl-d-aspartate (NMDA) dependent. The NMDA dependence suggested that substance P was acting postsynaptically. This was supported by the reduced variability of postsynaptic responses to glutamate by substance P. However, ultrastructural analyses suggested that there may also be a presynaptic component to the modulation, because substance P reduced the variability of synaptic vesicle diameters in putative glutamatergic terminals. These results suggest that cellular and synaptic variability can be targeted for modulation, making it an additional source of spinal cord plasticity.

Modeling the dentate gyrus

Computational modeling has become an increasingly useful tool for studying complex neuronal circuits such as the dentate gyrus. In order to effectively apply computational techniques and theories to answer pressing biological questions, however, it is necessary to develop detailed, data-driven models. Development of such models is a complicated process, akin to putting together a jigsaw puzzle with the pieces being such things as cell types, cell numbers, and specific connectivity. This chapter provides a walkthrough for the development of a very large-scale, biophysically realistic model of the dentate gyrus. Subsequently, it demonstrates the utility of a modeling approach in asking and answering questions about both healthy and pathological states involving the modeled brain region. Finally, this chapter discusses some predictions that come directly from the model that can be tested in future experimental approaches.

Retinoic acid delineates the topography of neuronal plasticity in postnatal cerebral cortex

Retinoic acid is well recognized to promote neuronal differentiation in the embryonic nervous system, but how it influences the postnatal cerebral cortex remains largely unknown. The domain of highest retinoic acid actions in the cortex of the mouse constricts postnatally to a narrow band that includes the dorsal visual stream and the attentional and executive networks. This band of cortex, which is distinguished by the retinoic acid-synthesizing enzyme RALDH3, exhibits signs of delayed maturation and enhanced plasticity compared to the surrounding cortex, as indicated by suppression of parvalbumin, neurofilament, cytochrome oxidase and perineuronal net maturation, and persistence of the embryonic, polysialated form of the neural cell-adhesion molecule PSA-NCAM. During the first postnatal week, the RALDH3-expressing territory translocates in the caudal cortex from the medial limbic lobe to the adjacent neocortex. This topographical shift requires the neurotrophin NT-3 because in mice lacking neuronal NT-3 the RALDH3 enzyme maintains its early postnatal pattern up to adulthood. In the NT-3-null mutants, expression of the markers, whose topography colocalizes with RALDH3 in the normal cortex, matches the abnormal RALDH3 pattern. This indicates that the uneven retinoic acid distribution serves a role in patterning the maturation and to some extent function of the normal postnatal cerebral cortex.

Variability, compensation and homeostasis in neuron and network function

Neurons in most animals live a very long time relative to the half-lives of all of the proteins that govern excitability and synaptic transmission. Consequently, homeostatic mechanisms are necessary to ensure stable neuronal and network function over an animal's lifetime. To understand how these homeostatic mechanisms might function, it is crucial to understand how tightly regulated synaptic and intrinsic properties must be for adequate network performance, and the extent to which compensatory mechanisms allow for multiple solutions to the production of similar behaviour. Here, we use examples from theoretical and experimental studies of invertebrates and vertebrates to explore several issues relevant to understanding the precision of tuning of synaptic and intrinsic currents for the operation of functional neuronal circuits.

Interneurons targeting similar layers receive synaptic inputs with similar kinetics

GABAergic interneurons play diverse and important roles in controlling neuronal network dynamics. They are characterized by an extreme heterogeneity morphologically, neurochemically, and physiologically, but a functionally relevant classification is still lacking. Present taxonomy is essentially based on their postsynaptic targets, but a physiological counterpart to this classification has not yet been determined. Using a quantitative analysis based on multidimensional clustering of morphological and physiological variables, we now demonstrate a strong correlation between the kinetics of glutamate and GABA miniature synaptic currents received by CA1 hippocampal interneurons and the laminar distribution of their axons: neurons that project to the same layer(s) receive synaptic inputs with similar kinetics distributions. In contrast, the kinetics distributions of GABAergic and glutamatergic synaptic events received by a given interneuron do not depend upon its somatic location or dendritic arborization. Although the mechanisms responsible for this unexpected observation are still unclear, our results suggest that interneurons may be programmed to receive synaptic currents with specific temporal dynamics depending on their targets and the local networks in which they operate.

SJ. Interneuron and pyramidal cell interplay during in vitro seizure-like events

Excitatory and inhibitory (EI) interactions shape network activity. However, little is known about the EI interactions in pathological conditions such as epilepsy. To investigate EI interactions during seizure-like events (SLEs), we performed simultaneous dual and triple whole cell and extracellular recordings in pyramidal cells and oriens interneurons in rat hippocampal CA1. We describe a novel pattern of interleaving EI activity during spontaneous in vitro SLEs generated by the potassium channel blocker 4-aminopyridine in the presence of decreased magnesium. Interneuron activity was increased during interictal periods. During ictal discharges interneurons entered into long-lasting depolarization block (DB) with suppression of spike generation; simultaneously, pyramidal cells produced spike trains with increased frequency (6-14 Hz) and correlation. After this period of runaway excitation, interneuron postictal spiking resumed and pyramidal cells became progressively quiescent. We performed correlation measures of cell-pair interactions using either the spikes alone or the subthreshold postsynaptic interspike signals. EE spike correlation was notably increased during interneuron DB, whereas subthreshold EE correlation decreased. EI spike correlations increased at the end of SLEs, whereas II subthreshold correlations increased during DB. Our findings underscore the importance of complex cell-type-specific neuronal interactions in the formation of seizure patterns.

Structure of cortical microcircuit theory

Recent experimental and theoretical investigations have made considerable advances in three major areas relating to the structural basis of quantitative cortical microcircuit theory. The first concerns the nature of the cellular units, encompassing the increasingly precise identification and progressively more complete listing of the individual cellular species that constitute the various cortical networks. The second element addresses the problem of heterogeneity, including the demonstration of the importance of cell to cell variability within defined interneuronal populations and the application of the Shannon-Wiener diversity index for the quantitative assessment of the number and relative abundance of interneuronal species. The third component relates to the discovery of basic topological principles underlying the circuit wiring, revealing a surprising order in the architectural design of networks. These new advances deepen our understanding of the computational principles embedded in cortical microcircuits, and they also provide novel opportunities for building realistic models of mammalian cortical microcircuits.