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Noda epileptic rat (NER) is a mutant model for epilepsy that exhibits spontaneous generalized tonic-clonic seizure. Epileptogenesis of NER remains to be elucidated; but it is detected an insertion of an endogenous retrovirus sequence in intron 2 of the PHD finger protein 24 (Phf24) gene, encoding Gαi-interacting protein (GINIP). Phf24 is a strong candidate gene for epileptogenesis in NER. PHF24 modulates GABAB signaling through interacting with Gαi protein. To clarify the epileptogenesis of NER, we investigated a distribution of PHF24-expressing cells in the central nerve system (CNS). While broad expression of PHF24 was observed in the CNS, characteristic expression was noted in the periglomerular layer of the olfactory bulb and the lamina II of the spinal cord in the control rats. These cells showed co-expression with calbindin or calretinin, inhibitory interneuron markers. In the olfactory bulb, 15.6% and 41.2% of PHF24-positive neurons co-expressed calbindin and calretinin, respectively. Immunoelectron microscopy revealed that PHF24 was located in the presynaptic terminals, synaptic membranes and cytoplasmic matrix of neuronal soma. Our data suggested PHF24 is expressed in the inhibitory interneurons and may play important roles in modulation of the GABAB signaling.

Experimental observations of simultaneous activity in large cortical areas have seemed to justify a large network approach in early studies of neural information codes and memory capacity. This approach has overlooked, however, the segregated nature of cortical structure and functionality. Employing graph-theoretic results, we show that, given the estimated number of neurons in the human brain, there are only a few primal sizes that can be attributed to neural circuits under probabilistically sparse connectivity. The significance of this finding is that neural circuits of relatively small primal sizes in cyclic interaction, implied by inhibitory interneuron potentiation and excitatory inter-circuit potentiation, generate relatively long non-repetitious sequences of asynchronous primal-length periods. The meta-periodic nature of such circuit interaction translates into meta-periodic firing-rate dynamics, representing cortical information. It is finally shown that interacting neural circuits of primal sizes 7 or less exhaust most of the capacity of the human brain, with relatively little room to spare for circuits of larger primal sizes. This also appears to ratify experimental findings on the human working memory capacity.

Maintaining an appropriate balance between excitation and inhibition is critical for neuronal information processing. Cortical neurons can cell-autonomously adjust the inhibition they receive to individual levels of excitatory input, but the underlying mechanisms are unclear. We describe that Ste20-like kinase (SLK) mediates cell-autonomous regulation of excitation-inhibition balance in the thalamocortical feedforward circuit, but not in the feedback circuit. This effect is due to regulation of inhibition originating from parvalbumin-expressing interneurons, while inhibition via somatostatin-expressing interneurons is unaffected. Computational modeling shows that this mechanism promotes stable excitatory-inhibitory ratios across pyramidal cells and ensures robust and sparse coding. Patch-clamp RNA sequencing yields genes differentially regulated by SLK knockdown, as well as genes associated with excitation-inhibition balance participating in transsynaptic communication and cytoskeletal dynamics. These data identify a mechanism for cell-autonomous regulation of a specific inhibitory circuit that is critical to ensure that a majority of cortical pyramidal cells participate in information coding.

The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity.

Dynamic causal modeling (DCM) is a method for analyzing functional magnetic resonance imaging (fMRI) and other functional neuroimaging data that provides information about directionality of connectivity between brain regions. A review of the neuropsychiatric fMRI DCM literature suggests that there may be a historical trend to under-report self-connectivity (within brain regions) compared to between brain region connectivity findings. These findings are an integral part of the neurologic model represented by DCM and serve an important neurobiological function in regulating excitatory and inhibitory activity between regions. We reviewed the literature on the topic as well as the past 13 years of available neuropsychiatric DCM literature to find an increasing (but still, perhaps, and inadequate) trend in reporting these results. The focus of this review is fMRI as the majority of published DCM studies utilized fMRI and the interpretation of the self-connectivity findings may vary across imaging methodologies. About 25% of articles published between 2007 and 2019 made any mention of self-connectivity findings. We recommend increased attention toward the inclusion and interpretation of self-connectivity findings in DCM analyses in the neuropsychiatric literature, particularly in forthcoming effective connectivity studies of substance use disorders.

A distinctive feature of the hippocampal structure is the diversity of inhibitory interneurons. These complex inhibitory interconnections largely contribute to the tight modulation of hippocampal circuitry, as well as to the formation and coordination of neuronal assemblies underlying learning and memory. Inhibitory interneurons provide more than a simple transitory inhibition of hippocampal principal cells (PCs). The synaptic plasticity of inhibitory neurons provides long-lasting changes in the hippocampal network and is a key component of memory formation. The dendrite targeting interneurons expressing the peptide somatostatin (SOM) are particularly interesting in this regard because they display unique long-lasting synaptic changes leading to metaplastic regulation of hippocampal networks. In this article, we examine the actions of the neuropeptide SOM on hippocampal cells, synaptic plasticity, learning, and memory. We address the different subtypes of hippocampal SOM interneurons. We describe the long-term synaptic plasticity that takes place at the excitatory synapses of SOM interneurons, its singular induction and expression mechanisms, as well as the consequences of these changes on the hippocampal network, learning, and memory. We also review evidence that astrocytes provide cell-specific dynamic regulation of inhibition of PC dendrites by SOM interneurons. Finally, we cover how, in mouse models of Alzheimer’s disease (AD), dysfunction of plasticity of SOM interneuron excitatory synapses may also contribute to cognitive impairments in brain disorders.

Summary Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (, Graphical abstract, Highlights • Inhibitory circuit population activity is organized on multiple spatiotemporal scales • Slow circuit-wide Golgi cell activation reflects general level of behavioral activity • Multidimensional differential population activity encodes behavioral information • Electrically coupled Golgi cell circuit model reproduces population-level properties, Inhibitory interneurons orchestrate the activity of neural circuits, but little is known about their population dynamics. By using 3D random-access calcium imaging, Gurnani and Silver show that cerebellar Golgi cell circuits exhibit multidimensional activity with common and distributed modes. A biologically detailed circuit model implicates electrical coupling in shaping the population dynamics.

SUMMARY Spinal interneurons are critical modulators of motor circuit function. In the dorsal spinal cord, a set of interneurons called GABApre presynaptically inhibits proprioceptive sensory afferent terminals, thus negatively regulating sensory-motor signaling. Although deficits in presynaptic inhibition have been inferred in human motor diseases, including dystonia, it remains unclear whether GABApre circuit components are altered in these conditions. Here, we use developmental timing to show that GABApre neurons are a late Ptf1a-expressing subclass and localize to the intermediate spinal cord. Using a microarray screen to identify genes expressed in this intermediate population, we find the kelch-like family member Klhl14, implicated in dystonia through its direct binding with torsion-dystonia-related protein Tor1a. Furthermore, in Tor1a mutant mice in which Klhl14 and Tor1a binding is disrupted, formation of GABApre sensory afferent synapses is impaired. Our findings suggest a potential contribution of GABApre neurons to the deficits in presynaptic inhibition observed in dystonia., In Brief GABApre spinal interneurons gate sensory inputs onto motor neurons. Zhang et al. localize GABApre neurons to the intermediate spinal cord and show that these interneurons express hereditary dystonia-related genes Klhl14 and Tor1a. In Tor1a mutant mice, GABApre synapse formation is disrupted, suggesting that spinal circuits may be affected in dystonia.

Inhibitory interneurons comprise only ∼20% of cortical neurons, but are essential for regulating many aspects of cortical function. These interneurons are generated embryonically from precursor cells in the subcortical medial and caudal ganglionic eminences. After their birth, the developing interneurons migrate to their cortex, differentiate, integrate into local microcircuits, and develop their adult physiological and synaptic properties over the course of weeks (mice) to years (humans). Data suggests that dysfunction of cortical maturation could play a significant role in numerous human neuropsychiatric diseases. As such, identification of the normal mechanisms of interneuron development as well as of the circuit implications of perturbation of interneuron function in adult life hold exceptional promise, both for developing novel treatments for human disease as well as for elucidating the evolutionary adaptations that allowed the phenomenal complexity of human neocortex. In this chapter, we describe the maturation of inhibitory interneuron physiology and the impact that these maturational changes have on the function and organization of the neocortex. Where available, we contrast the data in primates with that from mice, emphasizing the evolutionary adaptations of cortical interneurons. In addition, we discuss the impact of cortical activity on interneuron maturation and death.

SummaryNeuronal circuits face a fundamental tension between maintaining existing structure and changing to accommodate new information. Memory models often emphasize the need to encode novel patterns of neural activity imposed by “bottom-up” sensory drive. In such models, learning is achieved through synaptic alterations, a process which potentially interferes with previously stored knowledge 1-3. Alternatively, neuronal circuits generate and maintain a preconfigured stable dynamic, sometimes referred to as an attractor, manifold, or schema 4-7, with a large reservoir of patterns available for matching with novel experiences 8-13. Here, we show that incorporation of arbitrary signals is constrained by pre-existing circuit dynamics. We optogenetically stimulated small groups of hippocampal neurons as mice traversed a chosen segment of a linear track, mimicking the emergence of place fields 1,14,15, while simultaneously recording the activity of stimulated and non-stimulated neighboring cells. Stimulation of principal neurons in CA1, but less so CA3 or the dentate gyrus, induced persistent place field remapping. Novel place fields emerged in both stimulated and non-stimulated neurons, which could be predicted from sporadic firing in the new place field location and the temporal relationship to peer neurons prior to the optogenetic perturbation. Circuit modification was reflected by altered spike transmission between connected pyramidal cell – inhibitory interneuron pairs, which persisted during post-experience sleep. We hypothesize that optogenetic perturbation unmasked sub-threshold, pre-existing place fields16,17. Plasticity in recurrent/lateral inhibition may drive learning through rapid exploration of existing states.

Neuroscience Beyond down-regulating cortical activity, sleep also promotes long-term memory formation and the strengthening of synaptic connections. It is possible that both core sleep stages, slow-wave sleep (SWS) and rapid eye movement (REM) sleep, contribute to these processes. Niethard et al. used in vivo two-photon calcium imaging in mice to assess the activity of large populations of cortical layer 2/3 cells during SWS and REM sleep. Most pyramidal neurons substantially decreased their activity during SWS and REM sleep episodes. The decrease during SWS sleep, but not during REM sleep, was accompanied by increased inhibitory interneuron activity. However, a subpopulation of pyramidal cells exhibited upregulated activity during SWS. These neurons are possibly involved in memory formation, and also underwent profound down-regulation during subsequent REM sleep. J. Neurosci. , 41 , 4212 (2021).

Summary Sensory cues in the natural environment predict reward or punishment, important for survival. For example, the ability to detect attractive tastes indicating palatable food is essential for foraging while the recognition of inedible substrates prevents harm. While some of these sensory responses are innate, they can undergo fundamental changes due to prior experience associated with the stimulus. However, the mechanisms underlying such behavioral switching of an innate sensory response at the neuron and network levels require further investigation. We used the model learning system of Lymnaea stagnalis1, 2, 3 to address the question of how an anticipated aversive outcome reverses the behavioral response to a previously effective feeding stimulus, sucrose. Key to the switching mechanism is an extrinsic inhibitory interneuron of the feeding network, PlB (pleural buccal4,5), which is inhibited by sucrose to allow a feeding response. After multi-trial aversive associative conditioning, pairing sucrose with strong tactile stimuli to the head, PlB’s firing rate increases in response to sucrose application to the lips and the feeding response is suppressed; this learned response is reversed by the photoinactivation of a single PlB. A learning-induced persistent change in the cellular properties of PlB that results in an increase rather than a decrease in its firing rate in response to sucrose provides a neurophysiological mechanism for this behavioral switch. A key interneuron, PeD12 (Pedal-Dorsal 12), of the defensive withdrawal network5,6 does not mediate the conditioned suppression of feeding, but its facilitated output contributes to the sensitization of the withdrawal response., Graphical abstract, Highlights • Anticipation of an aversive outcome reverses the behavioral response to food. • The switching mechanism relies on an interneuron extrinsic to the feeding network. • Aversive learning causes persistent physiological change in this interneuron., Pirger et al. demonstrate that persistent modulation of an inhibitory interneuron extrinsic to the feeding system can switch the behavioral response so that a previously salient food stimulus elicits an aversive response. Anticipation of punishment associated with food induces excitation of an interneuron that inhibits the feeding network.

Inhibitory interneurons are the fundamental constituents of neural circuits that organize network outputs. The striatum as part of the basal ganglia is involved in reward-directed behaviors. However, the role of the inhibitory interneurons in this process remains unclear, especially in behaving monkeys. We recorded the striatal single neuron activity while monkeys performed reward-directed hand or eye movements. Presumed parvalbumin-containing GABAergic interneurons (fast-spiking neurons, FSNs) were identified based on narrow spike shapes in three independent experiments, though they were a small population (4.2%, 42/997). We found that FSNs are characterized by high-frequency and less-bursty discharges, which are distinct from the basic firing properties of the presumed projection neurons (phasically active neurons, PANs). Besides, the encoded information regarding actions and outcomes was similar between FSNs and PANs in terms of proportion of neurons, but the discharge selectivity was higher in PANs than that of FSNs. The coding of actions and outcomes in FSNs and PANs was consistently observed under various behavioral contexts in distinct parts of the striatum (caudate nucleus, putamen, and anterior striatum). Our results suggest that FSNs may enhance the discharge selectivity of postsynaptic output neurons (PANs) in encoding crucial variables for a reward-directed behavior.

SUMMARY In principle, one way to define the functional role of a neuron would be to identify all the synaptic input it receives and all synaptic output it confers onto its targets. With serial electron microscopy we annotated all the input synapses (862) and output synapses (626) associated with one inhibitory interneuron in the visual thalamus of the mouse. This neuron’s neurites covered a broad swath of lateral geniculate nucleus and spanned multiple functionally distinct regions. Every one of its neurites formed synapses onto hundreds of thalamocortical cells of several different types. All but one small neurite also had dendrite-like properties and received input from retinal ganglion cell axons. Pre- and postsynaptic associations with other inhibitory interneurons were also distributed throughout the interneuron’s territory. We observed a diverse array of local synaptic motifs and three fundamentally different types of inhibitory neurites. Many thalamocortical cells were innervated weakly by this interneuron by single en passant shaft synapses. But a subset of the interneuron’s thalamocortical cell targets received multiple synaptic inputs from targeted inhibitory neurites that climbed along the thalamocortical cell’s dendrite with an assemblage of fasciculated retinal ganglion cell axons. Because of the diverse range of synaptic relationships exhibited by this one neuron, this cell defies a single functional label and seems rather to be using extremely local synaptic processing to participate in many different functions.

Sensory perception depends on neocortical computations that contextually adjust sensory signals in different internal and environmental contexts. Neocortical layer 1 (L1) is the main target of cortical and subcortical inputs that provide “top-down” information for context-dependent sensory processing. Although L1 is devoid of excitatory cells, it contains the distal “tuft” dendrites of pyramidal cells (PCs) located in deeper layers. L1 also contains a poorly characterized population of GABAergic interneurons (INs), which regulate the impact that different top-down inputs have on PCs. A poor comprehension of L1 IN subtypes and how they affect PC activity has hampered our understanding of the mechanisms that underlie contextual modulation of sensory processing. We used novel genetic strategies in male and female mice combined with electrophysiological and morphological methods to help resolve differences that were unclear when using only electrophysiological and/or morphological approaches. We discovered that L1 contains four distinct populations of INs, each with a unique molecular profile, morphology, and electrophysiology, including a previously overlooked IN population (named here “canopy cells”) representing 40% of L1 INs. In contrast to what is observed in other layers, most L1 neurons appear to be unique to the layer, highlighting the specialized character of the signal processing that takes place in L1. This new understanding of INs in L1, as well as the application of genetic methods based on the markers described here, will enable investigation of the cellular and circuit mechanisms of top-down processing in L1 with unprecedented detail. SIGNIFICANCE STATEMENT Neocortical layer 1 (L1) is the main target of corticocortical and subcortical projections that mediate top-down or context-dependent sensory perception. However, this unique layer is often referred to as “enigmatic” because its neuronal composition has been difficult to determine. Using a combination of genetic, electrophysiological, and morphological approaches that helped to resolve differences that were unclear when using a single approach, we were able to decipher the neuronal composition of L1. We identified markers that distinguish L1 neurons and found that the layer contains four populations of GABAergic interneurons, each with unique molecular profiles, morphologies, and electrophysiological properties. These findings provide a new framework for studying the circuit mechanisms underlying the processing of top-down inputs in neocortical L1.

In recent years, schizophrenia research has focused on inhibitory interneuron dysfunction at the level of neurobiology and on cognitive impairments at the psychological level. Reviewing both experimental and computational findings, we show how the temporal structure of the activity of neuronal populations, exemplified by brain rhythms, can begin to bridge these levels of complexity. Oscillations in neuronal activity tie the pathophysiology of schizophrenia to alterations in local processing and large-scale coordination, and these alterations in turn can lead to the cognitive and perceptual disturbances observed in schizophrenia.

a b s t r a c t Cortical silent period (cSP) is a short interruption in electromyography (EMG) during active muscle contraction induced with transcranial magnetic stimulation (TMS). The cSP is a measure of cortical inhi- bition and is believed to represent inhibitory interneuron effects on excited motor cortical areas. Several pathological conditions and pharmacological manipulations induce changes to cSP duration indicating alterations in intracortical inhibition. At present, it is common to manually analyse the cSP duration from measured EMG. However, to avoid inter-examiner effects on cSP interpretation and detection, as well as to allow for quick measurement online, automated routine would be preferable. In this study, we evaluate the feasibility of a straight-forward cSP detection routine based on analysing the rectified first derivative of the EMG signal following TMS. Previously measured cSPs of 54 healthy subjects were reanalysed manually by two of the authors and using the automated routine. Furthermore, we recruited one subject for whom the cSPs were induced with several stimulation intensities, and those cSPs were analysed manually by two of the authors as well as using the automated routine. We found that cSPs were detected correctly by the automated cSP detection routine, and agreement with manually analysed subject-specific mean cSPs was excellent (ICC = 0.992, p < 0.001). The inter-examiner variability was sim- ilar to the variability between manual and automated analysis. Hence, we believe the introduced cSP detection routine would be feasible for online cSP detection, in such a way that is presently used to detect the motor evoked potentials.

Hodgkin and Huxley modeled the giant axon of the squid. Since then, many similar models of neurons in mammalian brains have been proposed. In this chapter, we list three examples, which will be used throughout the book.

Cortical neuronal network operations depend critically on the recruitment of GABAergic interneurons and the properties of their inhibitory output signals. Recent evidence indicates a marked difference in the signalling properties of two major types of perisomatic inhibitory interneurons, the parvalbumin- and the cholecystokinin-containing basket cells. Parvalbumin-expressing basket cells are rapidly recruited by excitatory synaptic inputs, generate high-frequency trains of action potentials, discharge single action potentials phase-locked to fast network oscillations and provide fast, stable and timed inhibitory output onto their target cells. In contrast, cholecystokinin-containing basket cells are recruited in a less reliable manner, discharge at moderate frequencies with single action potentials weakly coupled to the phases of fast network oscillations and generate an asynchronous, fluctuating and less timed inhibitory output. These signalling modes are based on cell type-dependent differences in the functional and plastic properties of excitatory input synapses, integrative qualities and in the kinetics and dynamics of inhibitory output synapses. Thus, the two perisomatic inhibitory interneuron types operate with different speed and precision and may therefore contribute differently to the operations of neuronal networks.

Odor enrichment enhances rats' ability to discriminate between chemically similar odorants. We show here that this modulation of olfactory perception is accompanied by increases in the density of local inhibitory interneuron expressing Zif268 in response to olfactory stimuli. These changes depend on the overlap of the olfactory bulb activation patterns induced by the enrichment odorants with those induced by the testing odorants, in a manner similar to changes in perception. Moreover, we show that enrichment leads to an alteration of the pattern of Zif268 expression, dependent on the odors used for the enrichment indicating a restructuring of odor representation in the olfactory bulb.

Animals generate movement by engaging spinal circuits that direct precise sequences of muscle contraction, but the identity and organizational logic of local interneurons that lie at the core of these circuits remain unresolved. Here, we show that V1 interneurons, a major inhibitory population that controls motor output, fractionate into highly diverse subsets on the basis of the expression of 19 transcription factors. Transcriptionally defined V1 subsets exhibit distinct physiological signatures and highly structured spatial distributions with mediolateral and dorsoventral positional biases. These positional distinctions constrain patterns of input from sensory and motor neurons and, as such, suggest that interneuron position is a determinant of microcircuit organization. Moreover, V1 diversity indicates that different inhibitory microcircuits exist for motor pools controlling hip, ankle, and foot muscles, revealing a variable circuit architecture for interneurons that control limb movement.

To determine the characteristics of high-frequency oscillations (HFOs) of cortical somatosensory evoked potentials (SEPs), the effect of general anesthesia on HFOs and low-frequency primary cortical responses was studied. The authors recorded SEPs elicited by median nerve stimulation directly from human brains of seven patients who underwent implantation of subdural electrodes before surgical treatment of intractable epilepsy. Recordings were made before and during general anesthesia. Changes in the number of HFOs and amplitude ratios of HFOs/primary cortical responses were analyzed. Under general anesthesia, the number of HFO peaks and the amplitude ratios were significantly decreased. General anesthesia induced remarkably decreased HFO activities when compared to low-frequency SEPs, suggesting that each of those originated from different generators. Possible relations between gamma-amino-butyric acid (GABA)ergic inhibitory interneurons and HFOs are discussed.

Intrahippocampal transplantation of inhibitory interneuron progenitors derived from the medial ganglionic eminence markedly ameliorates the seizure activity and neurobehavioral deficits typically observed in the pilocarpine mouse model of mesial temporal lobe epilepsy, even if the cells are engrafted after the onset of spontaneous seizures.

The hippocampus, a limbic brain region involved in the encoding and retrieval of memory, has a well-defined structural network assembled from excitatory principal neurons and inhibitory interneurons. Because the GABAergic interneurons form synapses onto both pyramidal neurons and interneurons, the activation of nicotinic acetylcholine receptors (nAChRs) present on certain interneurons could induce either inhibition or disinhibition in the hippocampal circuitry. To understand the role of nAChRs in controlling synaptic transmission in the hippocampus, we evaluated the magnitude of nAChR-modulated GABAergic postsynaptic currents (PSCs) in pyramidal neurons and various interneurons of the CA1 region. Using whole cell patch-clamp recording and post hoc identification of neuronal types in rat hippocampal slices, we show that brief (12-s) nAChR activation by ACh (1 mM) or choline (10 mM) enhances the frequency of GABAergic PSCs in both pyramidal neurons and CA1 interneurons. The magnitude of α7 nAChR-mediated GABAergic inhibition, as assessed by the net charge of choline-induced PSCs, was highest in stratum lacunosum moleculare interneurons followed by pyramidal neurons and s. radiatum interneurons. In contrast, the magnitude of α4β2 nAChR-mediated GABAergic inhibition, as assessed by the difference between the net charge of PSCs induced by ACh and choline, was highest in pyramidal neurons followed by s. lacunosum moleculare and s. radiatum interneurons. The present results suggest that cholinergic cues transmitted via specific subtypes of nAChRs modify the synaptic function in the hippocampus by inducing a differential degree of GABAergic inhibition in the target neurons.

Adding synaptic modification to the inhibitory interneuron in a minimal computational model of hippocampal region CA3 improves average performance of the simulations. After training on two partially overlapping sequences, simulations are tested on a sequence completion problem that can only be solved by using context dependent information. Simulations with dynamic autonomously scaling (DAS) inhibition are more robust than those without. In the DAS model, scaling factors for inhibition are adjusted gradually over time to compensate for the original model's tendency to move away from a pre-set activity level. This variable inhibition modifies more slowly than the local, associative synaptic modification of the excitatory synapses. As a result, activity fluctuations from one time-step to the next continue to occur, but average activity levels show small variability across training. These results suggest that restricting long term activity fluctuations can be beneficial to recurrent networks that must learn context dependent sequences.

This simulation study shows that with a simple network model the background function of a central pattern generator (CPG) network can be understood easily. The network model connects units consisting of two excitatory and one inhibitory population. An example of the lamprey demonstrates that a sufficient inhibition activity is necessary to produce CPG like patterns.

The type II unit is a prominent inhibitory interneuron in the dorsal cochlear nucleus (DCN), most likely recorded from vertical cells. Type II units are characterized by low rates of spontaneous activity, weak responses to broadband noise, and vigorous, narrowly tuned responses to tones. The weak responses of type II units to broadband stimuli are unusual for neurons in the lower auditory system and suggest that these units receive strong inhibitory inputs, most likely from onset-C neurons of the ventral cochlear nucleus. The question of the definition of type II units is considered here; the characteristics listed in the preceding text define a homogeneous type II group, but the boundary between this group and other low spontaneous rate neurons in DCN (type I/III units) is not yet clear. Type II units in decerebrate cats were studied using a two-tone paradigm to map inhibitory responses to tones and using noisebands of varying width to study the inhibitory processes evoked by broadband stimuli. Iontophoresis of bicuculline and strychnine and comparisons of two-tone responses between type II units and auditory nerve fibers were used to differentiate inhibitory processes occurring near the cell from two-tone suppression in the cochlea. For type II units, a significant inhibitory region is always seen with two-tone stimuli; the bandwidth of this region corresponds roughly to the previously reported excitatory bandwidth of onset-C neurons. Bandwidth widening experiments with noisebands show a monotonic decline in response as the bandwidth increases; these data are interpreted as revealing strong inhibitory inputs with properties more like onset-C neurons than any other response type in the lower auditory system. Consistent with these properties, iontophoresis of inhibitory antagonists produces a large increase in discharge rate to broadband noise, making tone and noise responses nearly equal.

Age-related impairments in the primary auditory cortex (A1) include poor tuning selectivity, neural desynchronization and degraded responses to low-probability or "oddball" sounds. These changes have been for the most part attributed to reduced inhibition in the aged brain. Since many of these changes can be partially reversed with auditory training, it has been speculated that they might not be purely degenerative but might rather represent negative plastic adjustments to noisy or distorted auditory inputs. To test this hypothesis, we exposed young adult rats to low-grade broadband noise for 6 weeks and then compared the effect of this exposure on several aspects of A1 function and structure. We found that the impact of noise exposure on A1 tuning selectivity and responses to oddball tones was almost indistinguishable from the effect of natural aging. These changes were paralleled by alterations in A1 inhibitory interneuron populations in the exposed group. Moreover we found that noise exposure reduced the anatomical and functional connectivity of A1 to downstream cortical fields. These results support the hypothesis that age-related changes in cortical auditory pathways might have a strong activity-dependent component, making them potentially preventable and reversible.

The mammalian telencephalon is responsible for many functions, which range from processing sensory information to learning, decision-making, and modulating emotional responses. The telencephalon's capacity to perform such a variety of functions likely relies on its neuronal diversity. Interneurons, with their enormous multiplicity of subtypes are a primary contributor to this repertoire. Each inhibitory interneuron subclass likely possesses both a unique connectivity and an input/output function that defines its diverse role in the telencephalon.

Even a simple sensory stimulus can elicit distinct innate behaviors and sequences. During sensorimotor decisions, competitive interactions among neurons that promote distinct behaviors must ensure the selection and maintenance of one behavior, while suppressing others. The circuit implementation of these competitive interactions is still an open question. By combining comprehensive electron microscopy reconstruction of inhibitory interneuron networks, modeling, electrophysiology, and behavioral studies, we determined the circuit mechanisms that contribute to the Drosophila larval sensorimotor decision to startle, explore, or perform a sequence of the two in response to a mechanosensory stimulus. Together, these studies reveal that, early in sensory processing, (1) reciprocally connected feedforward inhibitory interneurons implement behavioral choice, (2) local feedback disinhibition provides positive feedback that consolidates and maintains the chosen behavior, and (3) lateral disinhibition promotes sequence transitions. The combination of these interconnected circuit motifs can implement both behavior selection and the serial organization of behaviors into a sequence.

Amacrine and horizontal interneurons integrate visual information as it is relayed through the retina from the photoreceptors to the ganglion cells. The early steps that generate these interneuron networks remain unclear. Here we show that a distinct retinoid-related orphan nuclear receptor β1 (RORβ1) isoform encoded by the retinoid-related orphan nuclear receptor β gene (Rorb) is critical for both amacrine and horizontal cell differentiation in mice. A fluorescent protein cassette targeted into Rorb revealed RORβ1 as a novel marker of immature amacrine and horizontal cells and of undifferentiated, dividing progenitor cells. RORβ1-deficient mice lose expression of pancreas-specific transcription factor 1a (Ptf1a) but retain forkhead box n4 factor (Foxn4), two early-acting factors necessary for amacrine and horizontal cell generation. RORβ1 and Foxn4 synergistically induce Ptf1a expression, suggesting a central role for RORβ1 in a transcriptional hierarchy that directs this interneuron differentiation pathway. Moreover, ectopic RORβ1 expression in neonatal retina promotes amacrine cell differentiation.

Between 25–40% of neurons in laminae I–III are GABAergic, and some of these express neuropeptide Y (NPY). We previously reported that NPY-immunoreactive axons form numerous synapses on lamina III projection neurons that possess the neurokinin 1 receptor (NK1r). The aims of this study were to determine the proportion of neurons and GABAergic boutons in this region that contain NPY, and to look for evidence that they selectively innervate different neuronal populations. We found that 4–6% of neurons in laminae I–III were NPY-immunoreactive and based on the proportions of neurons that are GABAergic, we estimate that NPY is expressed by 18% of inhibitory interneurons in laminae I–II and 9% of those in lamina III. GABAergic boutons were identified by the presence of the vesicular GABA transporter (VGAT) and NPY was found in 13–15% of VGAT-immunoreactive boutons in laminae I–II, and 5% of those in lamina III. For both the lamina III NK1r-immunoreactive projection neurons and protein kinase Cγ (PKCγ)-immunoreactive interneurons in lamina II, we found that around one-third of the VGAT boutons that contacted them were NPY-immunoreactive. However, based on differences in the sizes of these boutons and the strength of their NPY-immunoreactivity, we conclude that these originate from different populations of interneurons. Only 6% of VGAT boutons presynaptic to large lamina I projection neurons that lacked NK1rs contained NPY. These results show that NPY-containing neurons make up a considerable proportion of the inhibitory interneurons in laminae I–III, and that their axons preferentially target certain classes of dorsal horn neuron. J. Comp. Neurol. 519:1007–1023, 2011. © 2010 Wiley-Liss, Inc.

International audience; In this article, we will review molecular, anatomical, physiological and pharmacological data in an attempt to better understand how excitatory and inhibitory neurons recruited by distinct afferent inputs to the cerebral cortex contribute to the coupled hemodynamic response, and how astrocytes can act as intermediaries to these neuronal populations. We aim at providing the pros and cons to the following statements that, depending on the nature of the afferent input to the neocortex, (i) different neuronal or astroglial messengers, likely acting in sequence, mediate the hemodynamic changes, (ii) some recruited neurons release messengers that directly alter blood vessel tone, (iii) others act by modulating neuronal and astroglial activity, and (iv) astrocytes act as intermediaries for both excitatory and inhibitory neurotransmitters. We will stress that a given afferent signal activates a precise neuronal circuitry that determines the mediators of the hemodynamic response as well as the level of interaction with surrounding astrocytes.

We consider a layer of excitatory neurons with small asymmetric excitatory connections and strong coupling to a single inhibitory interneuron. If the inhibition is fast, the network behaves as a winner-take-all network in which one cell fires at the expense of all others. As the inhibition slows down, oscillatory behavior begins. This is followed by a symmetric rotating solution in which neurons share the activity in a round-robin fashion. Finally, if the inhibition is sufficiently slower than excitation the neurons completely synchronize to a global periodic solution. Conditions guaranteeing stable synchrony are given.

Simulations were performed of physiological interactions among excitatory and inhibitory neurons in anatomically realistic local-circuit architectures modeled after hippocampal field CA1. The simulated circuitry consists of several excitatory neurons jointly innervating and receiving feedback from a common inhibitory interneuron. Excitatory cells in the simulation receive input during a cycle of naturally-occurring rhythmic activity (the hippocampal theta rhythm), and the neuron receiving the most input activation is the first to reach its spiking threshold. Spiking excites the inhibitory cell, which in turn prevents other cells from responding. The result is the natural generation of a simple competitive or ''winner-take-all'' (WTA) mechanism, allowing only the most strongly-activated cell in a group or ''patch'' to respond with spiking activity. Formal mathematical characterization of the mechanism reveals specific physiological characteristics of the input to the network, which enable it to closely approximate an ideal winner-take-all mechanism. Unlike other, more abstract WTA mechanisms that have been proposed, the parameters of this biologically-derived WTA mechanism can be directly related to specific physiological and anatomical features of particular cortical circuits.

In recent years, synaptic plasticity, which is dependent on the order and time interval of pre- and post-synaptic spikes, has been observed by physiological experiments. There are two types of STDP which are characterized by an asymmetric time window and a symmetric time window (mexican hat type window). A symmetric time window especially depends on the influence of an inhibitory neuron. In this paper, we investigate the synaptic circuit and the synaptic weight control circuit using STDP by inhibitory interneuron input or no input. As a result, we show that the synaptic circuit using STDP with the time windows of these two types could be constructed with a simple circuit configuration considering an inhibitory interneuron by using the circuit simulator PSpice. Furthermore, we show the characteristic of reinforcement and suppression.

The unpleasant sensation of pain plays an important protective role. Physiological, ‘fast’ pain warns us of imminent tissue damage and enables us to locate and withdraw from the source of injury. Later, inflammatory, ‘slow’ pain encourages protective immobilization of the injured area, which promotes tissue healing and functional recovery.

We study the transmission of excitatory synaptic inputs by a network of interneurons, coupled by electrical and inhibitory synapses, in the cases in which the network consists of three and four coupled units. It is shown that in both cases the network behaves as a coincidence detector.

Recent experiments show that inhibitory interneurons are coupled by electrical synapses. In this paper the information transmission properties of a network of three interneurons, coupled by electrical synapses alone, are studied by means of numerical simulations. It is shown that the network is capable to transfer the information contained in its presynapstic inputs when they are near synchronous: i.e. the network behaves as a coincidence detector. Thus, it is hypothesized that this property hold in general for networks of larger size. Lastly it is shown that these findings agree with recent experimental data.

We will consider the dynamics of attractor neural networks with sign-constrained weights. In the presense of sign-constraints on weights three types of attractor can affect the dynamics: retrieval attractors, spurious attractors and uniform attractors. The uniform attracting states can dominate the dynamics if there is a substantial weight-sign bias. We will show that it is possible to define dynamic thresholds for a variety of learning rules which can eliminate uniform attracting states for any value of the weight-sign bias.

Fast Spiking GABAergic interneurons, also coupled through gap junctions too, receive excitatory synaptic inputs from pyramidal cells and a relevant problem is to understand how their outputs depend on the timing of their inputs. In recent experiments it was shown that Fast Spiking interneurons respond with high temporal precision to synaptic inputs and are very sensitive to their synchrony level. In this paper this topic is investigated theoretically by using biophysical modelling of a pair of coupled Fast Spiking interneurons. In particular it is shown that, in agreement with the experimental findings, Fast Spiking interneurons transmit presynaptic signals with high temporal precision. Moreover, they are capable of reading and transferring high frequency inputs while preserving their relative timing. Lastly, a pair of Fast Spiking interneurons, coupled by both inhibitory and electrical synapses, behaves as a coincidence detector.

In recurrent neural networks, excessive activity oscillations can be very disruptive to successful learning performance. Inhibitory feedback can be used to offset a dominating positive feedback; however, synaptic modification at excitatory synapses would seem to require synaptic modification at inhibitory synapses if activity is to be controlled during training. Here, we present a novel synaptic modification rule that governs the synaptic strength of afferents (inputs) to activity controlling inhibitory interneurons. A hippocampal CA3 model incorporating this rule can avoid certain performance destroying activity oscillations. In the minimal model used here, this new rule for synaptic modification implements an error-correcting-like procedure at each excitatory input to a global feedback inhibitory interneuron. Simulations that include this novel modification rule demonstrate robust sequence learning as well as the elimination of major activity fluctuations that are outside the biologically plausible range. Importantly, simulations using this rule are able to adapt quickly and selectively to large, discontinuous jumps in the training sequences.

The brain is a very complex and very busy place. To narrow our inquiry about the connection between dopamine and attention it would be helpful to know just where D4Rs are located and how their location relates to attention. D4Rs are broadly distributed throughout the brain, rather than being highly localized in only one or two brain regions. Studies from the lab of Dr. Patricia Goldman-Rakic at Yale University showed that in the primate cortex D4Rs are particularly enriched in certain specific types of inhibitory interneurons (1), providing an important clue about where to look for the molecular events of human attention.

It is our deep reeling that Computational Neuroscience and Connectionist Engineering are in stagnancy and some fresh air is needed. The purpose oS this paper is to contribute to the description of the possible causes or this blockage: lack oS a new mathematics Sor plasticity, Sault tolerance, cooperative processes, and abstraction mechanisms to link the physical level to the cognitive processes. Also is clear that we have much more data than contributions to a realistic theory of the brain. As engineering we find again the lack of methodology, serious limitations of the Somal model underlying all the ANN paradigms and the necessity to end with the old rivalry between the symbolic and connectionist perspectives of AI.

The molecular mechanisms that provide humans with the capacity for attention and attention-based learning are necessarily somewhat complex to understand. If they were simple we would have figured them out long ago. That’s the bad news. The good news is that the mechanisms aren’t so complex that we can’t learn to understand them. Sure the brain is the most complexly organized structure in the body and even the most sophisticated computers currently available don’t come close to reproducing its abilities. Nonetheless we can harness our own powers of attention to focus in on those particular aspects which specifically relate to attention. There is a vast amount of neuroscientific knowledge providing clues for solving this puzzle and recent breakthroughs create a new framework for understanding attention.

A seizure involves the synchronization of the activity of a very large population of periodically firing neurons [4,483]. It is well known that periodic electrical or sensory stimulation can be used to trigger the onset of a seizure. Here we discuss the use of periodic stimuli to abort seizures once they are occurring.

The complex motor activities of higher organisms are mediated through the activation of muscles by their respective motoneurons (the final common path). Motor responses are categorized according to their complexity, and the degree to which they are under conscious control.