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Understanding the neurovascular coupling (NVC) underlying hemodynamic changes in epilepsy is crucial to properly interpreting functional brain imaging signals associated with epileptic events. However, how excitatory and inhibitory neurons affect vascular responses in different epileptic states remains unknown. We conducted real-time in vivo measurements of cerebral blood flow (CBF), vessel diameter, and excitatory and inhibitory neuronal calcium signals during recurrent focal seizures. During preictal states, decreases in CBF and arteriole diameter were closely related to decreased γ-band local field potential (LFP) power, which was linked to relatively elevated excitatory and reduced inhibitory neuronal activity levels. Notably, this preictal condition was followed by a strengthened ictal event. In particular, the preictal inhibitory activity level was positively correlated with coherent oscillating activity specific to inhibitory neurons. In contrast, ictal states were characterized by elevated synchrony in excitatory neurons. Given these findings, we suggest that excitatory and inhibitory neurons differentially contribute to shaping the ictal and preictal neural states, respectively. Moreover, the preictal vascular activity, alongside with the γ-band, may reflect the relative levels of excitatory and inhibitory neuronal activity, and upcoming ictal activity. Our findings provide useful insights into how perfusion signals of different epileptic states are related in terms of NVC.

We here study a network of synaptic relations mingling excitatory and inhibitory neuron nodes that displays oscillations quite similar to electroencephalogram (EEG) brain waves, and identify abrupt variations brought about by swift synaptic mediations. We thus conclude that corresponding changes in EEG series surely come from the slowdown of the activity in neuron populations due to synaptic restrictions. The latter happens to generate an imbalance between excitation and inhibition causing a quick explosive increase of excitatory activity, which turns out to be a (first-order) transition among dynamic mental phases. Moreover, near this phase transition, our model system exhibits waves with a strong component in the so-called delta-theta domain that coexist with fast oscillations. These findings provide a simple explanation for the observed delta-gamma and theta-gamma modulation in actual brains, and open a serious and versatile path to understand deeply large amounts of apparently erratic, easily accessible brain data., Spanish Ministry of Science and Technology, Agencia Española de Investigación (AEI), FEDER - FIS2017-84256-P, Consejería de Conocimiento, Investigación Universidad, Junta de Andalucía and European Regional Development Funds, Spain - SOMM17/6105/UGR Y A-FQM-175-UGR18, Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía and European Regional Development Funds, Ref. P20_00173

The inferior colliculus (IC) is a large midbrain nucleus that integrates inputs from many auditory brainstem and cortical structures. Despite its prominent role in auditory processing, the various cell types and their connections within the IC are not well characterized. To further separate GABAergic and non-GABAergic neuron types according to their physiological properties, we used a mouse model that expresses channelrhodopsin and enhanced yellow fluorescent protein in all GABAergic neurons and allows identification of GABAergic cells by light stimulation. Neuron types were classified upon electrophysiological measurements of the hyperpolarizing-activated current ( Ih) in acute brain slices of young adult mice. All GABAergic neurons from our sample displayed slow-activating Ih with moderate amplitudes, whereas a subset of excitatory neurons showed fast-activating Ih with large amplitudes. This is in agreement with our finding that immunoreactivity against the fast-gating hyperpolarization-activated and cyclic-nucleotide-gated 1 (HCN1) channel was present around excitatory neurons, whereas the slow-gating HCN4 channel was found perisomatically around most inhibitory neurons. Ih properties and neurotransmitter types were correlated with firing patterns to depolarizing current pulses. All GABAergic neurons displayed adapting firing patterns very similar to the majority of glutamatergic neurons. About 15% of the glutamatergic neurons showed an onset spiking pattern, always in combination with large and fast Ih. We conclude that HCN channel subtypes are differentially distributed in IC neuron types and correlate with neurotransmitter type and firing pattern. In contrast to many other brain regions, membrane properties and firing patterns were similar in GABAergic neurons and about one-third of the excitatory neurons. NEW & NOTEWORTHY Neuron types in the central nucleus of the auditory midbrain are not well characterized regarding their transmitter type, ion channel composition, and firing pattern. The present study shows that GABAergic neurons have slowly activating hyperpolarizing-activated current ( Ih) and an adaptive firing pattern whereas at least four types of glutamatergic neurons exist regarding their Ih properties and firing patterns. Many of the glutamatergic neurons were almost indistinguishable from the GABAergic neurons regarding Ih properties and firing pattern.

SUMMARY Many factors modulate the state of cortical activity, but the importance of cortical state variability for sensory perception remains debated. We trained mice to detect spatially localized visual stimuli and simultaneously measured local field potentials and excitatory and inhibitory neuron populations across layers of primary visual cortex (V1). Cortical states with low spontaneous firing and correlations in excitatory neurons, and suppression of 3- to 7-Hz oscillations in layer 4, accurately predicted single-trial visual detection. Our results show that cortical states exert strong effects at the initial stage of cortical processing in V1 and can play a prominent role for visual spatial behavior in mice., Graphical Abstract, In Brief Speed et al. show that visual behavior in mice is strongly influenced by the state of activity in primary visual cortex (V1). Single-trial perceptual accuracy was highly predictable from oscillations in the input layers and from correlations between excitatory neurons.

Oscillatory rhythms are investigated in a model network where a pair of excitatory neurons interact via an inhibitory neuron. Each individual neuron is modeled as a relaxation oscillator, and a slo...

CD40-activated CD40L-mediated reverse signalling is a major physiological regulator of neurite growth from excitatory and inhibitory neurons in the developing central nervous system (CNS). Whereas in excitatory pyramidal neurons, CD40L reverse signalling promotes the growth and elaboration of dendrites and axons, in inhibitory GABAergic striatal medium spiny neurons (MSNs), it restricts neurite growth and branching. In pyramidal neurons, we previously reported that CD40L reverse signalling activates an interconnected and interdependent signalling network involving protein kinase C (PKC), extracellular regulated kinases 1 and 2 (ERK1/2), and c-Jun N-terminal kinase (JNK) signalling pathways that regulates dendrite and axon growth. Here, we have studied whether these signalling pathways also influence neurite growth from striatal inhibitory MSNs. To unequivocally activate CD40L reverse signalling, we treated MSN cultures from CD40-deficient mice with CD40-Fc. Here, we report that activation of CD40L reverse signalling in these cultures also increased the phosphorylation of PKC, ERK1/2, and JNK. Using pharmacological activators and inhibitors of these signalling pathways singularly and in combination, we have shown that, as in pyramidal neurons, these signalling pathways work in an interconnected and interdependent network to regulate the neurite growth, but their functions, relationships, and interdependencies are different from those observed in pyramidal neurons. Furthermore, immunoprecipitation studies showed that stimulation of CD40L reverse signalling recruits the catalytic fragment of Syk tyrosine kinase, but in contrast to pyramidal neurons, PKC does not participate in this recruitment. Our findings show that distinctive networks of three signalling pathways mediate the opposite effects of CD40L reverse signalling on neurite growth in excitatory and inhibitory neurons.

The units in artificial neural networks (ANNs) can be thought of as abstractions of biological neurons, and ANNs are increasingly used in neuroscience research. However, there are many important differences between ANN units and real neurons. One of the most notable is the absence of Dale’s principle, which ensures that biological neurons are either exclusively excitatory or inhibitory. Dale’s principle is typically left out of ANNs because its inclusion impairs learning. This is problematic, because one of the great advantages of ANNs for neuroscience research is their ability to learn complicated, realistic tasks. Here, by taking inspiration from feedforward inhibitory interneurons in the brain we show that we can develop ANNs with separate populations of excitatory and inhibitory units that learn just as well as standard ANNs. We call these networks Dale’s ANNs (DANNs). We present two insights that enable DANNs to learn well: (1) DANNs are related to normalization schemes, and can be initialized such that the inhibition centres and standardizes the excitatory activity, (2) updates to inhibitory neuron parameters should be scaled using corrections based on the Fisher Information matrix. These results demonstrate how ANNs that respect Dale’s principle can be built without sacrificing learning performance, which is important for future work using ANNs as models of the brain. The results may also have interesting implications for how inhibitory plasticity in the real brain operates.

The presence of male-female brain differences has long been a controversial topic. Yet simply negating the existence of biological differences has detrimental consequences for all sexes and genders, particularly for the development of accurate diagnostic tools, effective drugs and understanding of disease. The most well-established morphological difference is size, with males having on average a larger brain than females; yet a mechanistic understanding of how this difference arises remains to be elucidated. Here, we use brain organoids to test the roles of sex chromosomes and sex steroids during development. While we show no observable differences between XX and XY brain organoids, sex steroids, namely androgens, increase proliferation of cortical neural progenitors. Transcriptomic analysis reveals effects on chromatin remodelling and HDAC activity, both of which are also implicated in the male-biased conditions autism spectrum disorder and schizophrenia. Finally, we show that higher numbers of progenitors result specifically in increased upper-layer excitatory neurons. These findings uncover a hitherto unknown role for male sex hormones in regulating excitatory neuron number within the human neocortex and represent a first step towards understanding the origin of human sex-related brain differences.

We designed, simulated, prototyped, and experimentally demonstrated an optoelectronic neuron with excitatory and inhibitory inputs. LTSpice simulation and experimental results closely resemble the Izhikevich model, and inhibitory input negates excitatory input to suppress output spikes.

OBJECTIVE Intracellular recordings from cells in entorhinal cortex tissue slices show that low-voltage fast (LVF) onset seizures are generated by inhibitory events. Here, we determined whether increased firing of interneurons occurs at the onset of spontaneous mesial-temporal LVF seizures recorded in patients. METHODS The seizure onset zone (SOZ) was identified using visual inspection of the intracranial electroencephalogram. We used wavelet clustering and temporal autocorrelations to characterize changes in single-unit activity during the onset of LVF seizures recorded from microelectrodes in mesial-temporal structures. Action potentials generated by principal neurons and interneurons (ie, putative excitatory and inhibitory neurons) were distinguished using waveform morphology and K-means clustering. RESULTS From a total of 200 implanted microelectrodes in 9 patients during 13 seizures, we isolated 202 single units; 140 (69.3%) of these units were located in the SOZ, and 40 (28.57%) of them were classified as inhibitory. The waveforms of both excitatory and inhibitory units remained stable during the LVF epoch (p > > 0.05). In the mesial-temporal SOZ, inhibitory interneurons increased their firing rate during LVF seizure onset (p

The mechanisms of interictal discharges (IID) were studied under the conditions of the 4-aminopyridine model of spontaneous epileptiform activity in surviving rat brain slice preparations. Addition of the agents blocking GABA and NMDA receptors failed to inhibit IID generation in the entorhinal cortex. A mathematical model of IID has been developed on the basis of the excitatory neuron interaction mediated by the AMPA receptor. Short-term synaptic depression and slow afterspike-hyperpolarization are the key factors required to terminate a single IID. The IID shape-determining factors have been identified. The experimental and model IID features correspond to each other.

Neocortical inhibitory neurons exhibit remarkably diverse morphology, physiological properties and connectivity. Genetic access to molecularly-defined subtypes of inhibitory neurons has aided their functional characterization in recent years. These studies have established that, instead of simply balancing excitatory neuron activity, inhibitory neurons actively shape excitatory circuits in a subtype-specific manner. We review the emerging view that inhibitory neuron subtypes perform context-dependent modulation of excitatory activity as well as regulate experience-dependent plasticity of excitatory circuits. We then review the roles of neuromodulators in regulating the subtype-specific functions of inhibitory neurons. Finally, we discuss the notion that dysfunctions of inhibitory neuron subtypes may be responsible for various aspects of neurological disorders.

SummaryMany factors modulate the state of cortical activity, but the importance of cortical states for sensory perception remains debated. We trained mice to detect spatially localized visual stimuli, and simultaneously measured local field potentials and excitatory and inhibitory neuron populations across layers of primary visual cortex (V1). Cortical states with low firing rates and correlations between excitatory neurons, and reduced oscillatory activity in Layer 4, accurately predicted single trials of visual spatial detection behavior. Our results show that cortical states exert strong effects at the initial stage of cortical processing in V1, and play a decisive role for visual spatial behavior in mice.

Spontaneous respiratory rhythmic burst activity can be preserved in the preBotzinger Complex (preBotC) of rodent medullary transverse slices. It is known, that the activation sequence of inspiratory neurons in the preBotC stochastically varies from cycle to cycle. To test whether the activation timing of an inspiratory neuron depends on its neurotransmitter, we performed calcium imaging of preBotC neurons using double-transgenic mice expressing EGFP in GlyT2+ neurons and tdTomato in GAD65+ neurons. Five types of inspiratory neurons were identified using the fluorescence protein expression and the maximum cross-correlation coefficient between neuronal calcium fluctuation and field potential. Regarding the activation sequence, irregular type putative excitatory (GlyT2-/GAD65-) neurons and irregular type glycinergic (GlyT2+/GAD65-) neurons tended to be activated early, while regular type putative excitatory neurons, regular type glycinergic neurons tended to be activated later. In conclusion, the different cell types define a general framework for the stochastically changing activation sequence of inspiratory neurons in the preBotC.

For a class of excitatory spiking neuron models with delayed feedback fed with a Poisson stochastic process, it is proven that the stream of output interspike intervals cannot be presented as a Markov process of any order. Keywords: spiking neuron; Poisson stochastic process; probability density function; delayed feedback; non-Markov stochastic process, 15 pages, 2 figures, 25 Refs

The axons forming the corpus callosum sustain the interhemispheric communication across homotopic cortical areas. We have studied how neurons throughout the columnar extension of the retrosplenial cortex integrate the contralateral input from callosal projecting neurons in cortical slices. Our results show that pyramidal neurons in layers 2/3 and the large, thick-tufted pyramidal neurons in layer 5B showed larger excitatory callosal responses than layer 5A and layer 5B thin-tufted pyramidal neurons, while layer 6 remained silent to this input. Feed-forward inhibitory currents generated by fast spiking, parvalbumin expressing interneurons recruited by callosal axons mimicked the response size distribution of excitatory responses across pyramidal subtypes, being larger in those of superficial layers and in the layer 5B thick-tufted pyramidal cells. Overall, the combination of the excitatory and inhibitory currents evoked by callosal input had a strong and opposed effect in different layers of the cortex; while layer 2/3 pyramidal neurons were powerfully inhibited, the thick-tufted but not thin-tufted pyramidal neurons in layer 5 were strongly recruited. We believe that these results will help to understand the functional role of callosal connections in physiology and disease., This work was supported by: Spanish Ministerio de Ciencia e Innovación (Severo Ochoa program, Grant SEV-2013-0317; Fondos FEDER SAF2014-59347-C2-1-R) and Generalitat Valenciana (PROMETEO II program Grant 2014/014). ASF was supported by a JAE-PREDOC Grant (CSIC, BOE-A-2011-10745).

The distinctive firing pattern of grid cells in the medial entorhinal cortex (MEC) supports its role in the representation of space. It is widely believed that the hexagonal firing field of grid cells emerges from neural dynamics that depends on the local microcircuitry. However, local networks within the MEC are still not sufficiently characterized. Here, applying up to eight simultaneous whole-cell recordings in acute brain slices, we demonstrate the existence of unitary excitatory connections between principal neurons in the superficial layers of the MEC. In particular, we find prevalent feed-forward excitation from pyramidal neurons in layer III and layer II onto stellate cells in layer II, which might contribute to the generation or the inheritance of grid-cell patterns.

Competitive interactions are believed to underlie many types of cortical processing, ranging from memory formation, attention and development of cortical functional organization (e.g., development of orientation maps in primary visual cortex). In the latter case, the competitive interactions happen along the cortical surface, with local populations of neurons reinforcing each other, while competing with those displaced more distally. This specific configuration of lateral interactions is however in stark contrast with the known properties of the anatomical substrate, i.e., excitatory connections (mediating reinforcement) having longer reach than inhibitory ones (mediating competition). No satisfactory biologically plausible resolution of this conflict between anatomical measures, and assumed cortical function has been proposed. Recently a specific pattern of delays between different types of neurons in cat cortex has been discovered, where direct mono-synaptic excitation has approximately the same delay, as the combined delays of the disynaptic inhibitory interactions between excitatory neurons (i.e., the sum of delays from excitatory to inhibitory and from inhibitory to excitatory neurons). Here we show that this specific pattern of delays represents a biologically plausible explanation for how short-range inhibition can support competitive interactions that underlie the development of orientation maps in primary visual cortex. We demonstrate this statement analytically under simplifying conditions, and subsequently show using network simulations that development of orientation maps is preserved when long-range excitation, direct inhibitory to inhibitory interactions, and moderate inequality in the delays between excitatory and inhibitory pathways is added.

Memory loss in Alzheimer’s disease (AD) is attributed to pervasive weakening and loss of synapses. Here, we present findings supporting a special role for excitatory synapses connecting pyramidal neurons of the hippocampus and cortex with fast-spiking parvalbumin (PV) interneurons that control network excitability and rhythmicity. Excitatory synapses on PV interneurons are dependent on the AMPA receptor subunit GluA4, which is regulated by presynaptic expression of the synaptogenic immediate early gene NPTX2 by pyramidal neurons. In a mouse model of AD amyloidosis, Nptx2-/- results in reduced GluA4 expression, disrupted rhythmicity, and increased pyramidal neuron excitability. Postmortem human AD cortex shows profound reductions of NPTX2 and coordinate reductions of GluA4. NPTX2 in human CSF is reduced in subjects with AD and shows robust correlations with cognitive performance and hippocampal volume. These findings implicate failure of adaptive control of pyramidal neuron-PV circuits as a pathophysiological mechanism contributing to cognitive failure in AD.

When populations of excitatory and inhibitory neurons are synaptically connected, oscillations often emerge. The reason is apparent: Activity of the excitatory neurons (which we will call E-cells from here on, as we did in Chapter 22) generates activity of the inhibitory neurons (I-cells). The activity of the I-cells causes the activity of the E-cells to cease transiently, and when it resumes, the E-cell population is closer to synchrony, as discussed in Chapter 29 The oscillations in Chapter 22 are of a similar nature, although there individual cells were not modeled. Figure 30.1 (nearly identical with Fig. 22.1) represents the interaction of E- and I-cells symbolically.

The local field potential (LFP) is generated by large populations of neurons, but unitary contribution of spiking neurons to LFP is not well characterised. We investigated this contribution in multi-electrode array recordings from human and monkey neocortex by examining the spike-triggered LFP average (st-LFP). The resulting st-LFPs were dominated by broad spatio-temporal components due to ongoing activity, synaptic inputs and recurrent connectivity. To reduce the spatial reach of the st-LFP and observe the local field related to a single spike we applied a spatial filter, whose weights were adapted to the covariance of ongoing LFP. The filtered st-LFPs were limited to the perimeter of 800 μm around the neuron, and propagated at axonal speed, which is consistent with their unitary nature. In addition, we discriminated between putative inhibitory and excitatory neurons and found that the inhibitory st-LFP peaked at shorter latencies, consistently with previous findings in hippocampal slices. Thus, in human and monkey neocortex, the LFP reflects primarily inhibitory neuron activity.

The dynamics of spontaneous and sensory-evoked up-states have been recently compared, in multi-site recordings in vivo and found to have similarities and differences. Also in vitro , this is evident because we here describe a novel computational method to classify into statistically different states the spontaneous reverberating activity recorded from long-term (12–18 days- in vitro) cultured cortical neurons (from 60-site m ulti- e lectrode a rrays, MEA). State classification was performed by s pike n umber t ime h istograms (SNTH, or other burst features) of excitatory and inhibitory neuron clusters and revealed that in novel identified states the number of engaged neurons or up-state duration can change. To improve the characterization of each state we also computed the f iring s pike h istograms (FSH) which revealed a new facet of the firing probability of clusters. In exemplary functional experiments we show that: (i) up to 6–7 states can be safely categorized during several hours of recordings without observing spike rate changes, (ii) they disappear after a short pharmacological stimulation being replaced with novel states active and living up to 6–8 h, (iii) antagonists in the nM range can split the activity of a homogeneous network into the chronological coexistence of 2 states, one completely different and one not significantly different from control state. In conclusion, we believe that this novel procedure better characterizes the number of functional states of a network and opens up the possibility of predicting the elementary “vocabulary” used by small networks of neurons.

The aim of this study was to determine the morphology and position of the excitatory and inhibitory motor neurons to the human gastric sling and clasp fibers. Motor neurons were identified by retrograde staining with 1,1′-didodecyl 3,3,3′,3′-indocarbocyanine perchlorate (DiI), and choline acetyltransferase (ChAT) or nitric oxide synthase (NOS) immunoreactivity was then determined in these motor neurons. In the sling preparations, 46% of the DiI-stained cells were aboral motor neurons, 43% were local motor neurons, and only 10% were descending motor neurons. Overall, 58% were immunoreactive for ChAT, and 36% for NOS (P = 0.042). Sixty-two percent of local, and 66% of aboral DiI-stained motor neurons were immunoreactive for ChAT. In the clasp preparations, 52% of the DiI-stained cells were descending motor neurons, 45% were local motor neurons, and only 3% were aboral neurons. Overall, 31% were immunoreactive for ChAT and 65% for NOS (P = 0.039). Eighty-five percent of the DiI-stained descending motor neurons were immunoreactive for NOS. All of the cells that were labeled adequately had a single axon and a number of filamentous or flattened lobular dendrites, and fitted into the broad category of Dogiel type I neurons. In conclusion, the majority of the motor neurons to the sling fibers were ChAT-positive excitatory neurons from the myenteric plexus of the stomach and the local region, and to the clasp were predominantly NOS-positive inhibitory neurons from the esophagus.

A stochastic model of neuronal population with excitatory and inhibitory connections is proposed, where excitatory synaptic dynamics is considered. Oscillatory synchronized firing patterns of a neuronal population by means of firing density are investigated. Numerical simulations using Fokker–Planck equation show that slow inhibitory connection contributes to oscillatory synchronized firing of the neuronal population, and synchronous activity is enhanced due to inhibitory connection. The effect of time delay on the oscillatory synchronized firing in the neuronal population using phase mode is explored. Numerical simulation indicates that short synaptic transmission delay can suppress oscillatory synchronized firing, but this suppression is instable.

An excitatory-inhibitory recurrent neuronal network is established to numerically study the effect of inhibitory neurons on the synchronization degree of neuronal systems. The obtained results show that, with the number of inhibitory neurons and the coupling strength from an inhibitory neuron to an excitatory neuron increasing, inhibitory neurons can not only reduce the synchronization degree when the synchronization degree of the excitatory population is initially higher, but also enhance it when it is initially lower. Meanwhile, inhibitory neurons could also help the neuronal networks to maintain moderate synchronized states. In this paper, we call this effect as modulation effect of inhibitory neurons. With the obtained results, it is further revealed that the ratio of excitatory neurons to inhibitory neurons being nearly 4 : 1 is an economic and affordable choice for inhibitory neurons to realize this modulation effect.

We analyzed the oscillatory activities in a neuronal network model as the basis of synchrony of the activities in the brain. The model consists of two groups of neurons that are interconnected. One group is composed of an excitatory and an inhibitory neuron which are expressed by Hodgkin–Huxley equations. The network shows different phase-locked oscillations and other activities depending on the structure and intensity of interconnection between groups or coupling of neurons in the group, or the value of transmission latency. In the present paper we show the oscillatory modes in symmetrical and asymmetrical networks with the mutual coupling from the inhibitory neuron in each group to the excitatory neuron in the other group.

Cortical circuits transform neural information within a stereotyped laminar architecture. These operations require the coordinated activity of excitatory and inhibitory neurons. Inhibitory GABAergi...

In a network of an excitatory and an inhibitory neuron, depression in the inhibitory synapse can produce two distinct oscillatory regimes. In one regime, the network has a short period cell-dominated solution; in the other regime, the solution has much longer period and is synapse-dominated. These regimes overlap to produce an interval of bistability. Neuromodulatory input that targets one of multiple parameters in the network can switch the network control between the intrinsic properties of cells and the dynamics of the synapses.

1. Microiontophoresis of gamma-aminobutyric acid was used to reversibly inactivate small sites of defined orientation and direction specificity at a horizontal distance of 400-700 microns from single cells recorded in cat area 18. There was extensive or complete overlap between the receptive fields of cells at the recording and inactivation sites. A cell's directionality index [DI: 1 - (response to nonpreferred direction/response to preferred direction)], the response to the preferred direction, and orientation tuning width (measured at half the maximum response) were compared before and during inactivation of either iso-orientation sites (where the orientation preference was within 22.5 degrees) or cross-orientation sites (where it differed by 45-90 degrees). 2. During iso-orientation inactivation, 40 (73%) of 55 cells showed a significant (> 0.20) change in DI; the mean change in DI for these cells was 0.59. An additional cell showed a marked increase in response to the preferred direction that did not result in a change in DI. With one exception, the effects occurred in the absence of a significant (> 25%) change in orientation tuning width. 3. In most cases, the results were broadly predictable in the sense that iso-orientation inactivation predominantly affected a cell's response to the direction of motion of an optimally oriented bar that was closest to the preferred direction at the inactivation site: viz., a decrease in response to the preferred direction and an increase in response to the preferred or nonpreferred direction. 4. It is argued that the decreases in response were due to a reduction in the strength of intracortical iso-orientation excitatory connections made primarily between cells with similar direction preferences, whereas the increases in response involved a loss of iso-orientation inhibition. 5. In cases where remote inactivation caused an increase in response to the nonpreferred direction, comparable effects could be elicited when a mask left exposed only the excitatory subregion of the receptive field in S cells or the most responsive part of the excitatory discharge region in C cells. This implies extensive or complete spatial overlap between the profiles of excitation and inhibition in a cell's nonpreferred direction. 6. During cross-orientation inactivation, a significant change in DI was seen in only 14 (19%) of 73 cells and, with one exception, these changes were accompanied by increases in response to non-optimal orientations and significant broadening of orientation tuning. The effects of cross-orientation inactivation on directionality were presumably due to the loss of cross-orientation inhibition, which contributes primarily to orientation tuning. 7. Inactivation of the same site could cause an increase in response to the nonpreferred direction in cells recorded at iso-orientation sites and an increase in response to nonoptimal orientations and broadening of orientation tuning in cells recorded at cross-orientation sites. This is consistent with the notion that a single inhibitory neuron can contribute to the directionality or orientation tuning of different target cells depending on their location in the orientation map. 8. The results provide evidence for a major contribution of intrinsic mechanisms to the orientation tuning and direction selectivity of cells in cat area 18. It is proposed that two different intracortical processes are involved in the enhancement of orientation and direction selectivity: 1) suppression of responses to nonoptimal orientations and directions as a result of cross-orientation inhibition and iso-orientation inhibition; and 2) facilitation of responses to optimal orientations/directions via iso-orientation excitatory connections.

Models of cortical neuronal circuits commonly depend on inhibitory feedback to control gain, provide signal normalization, and to selectively amplify signals using winner-take-all (WTA) dynamics. Such models generally assume that excitatory and inhibitory neurons are able to interact easily, because their axons and dendrites are co-localized in the same small volume. However, quantitative neuroanatomical studies of the dimensions of axonal and dendritic trees of neurons in the neocortex show that this co-localization assumption is not valid. In this paper we describe a simple modification to the WTA circuit design that permits the effects of distributed inhibitory neurons to be coupled through synchronization, and so allows a single WTA to be distributed widely in cortical space, well beyond the arborization of any single inhibitory neuron, and even across different cortical areas. We prove by non-linear contraction analysis, and demonstrate by simulation that distributed WTA sub-systems combined by such inhibitory synchrony are inherently stable. We show analytically that synchronization is substantially faster than winner selection. This circuit mechanism allows networks of independent WTAs to fully or partially compete with each other., in press at Neural computation; 4 figures

An essential feature of the mammalian cerebral cortex is the sequential establishment of excitatory–inhibitory neuronal assemblages between pyramidal and local-circuit inhibitory neurons. The recognition, location, and distribution of these excitatory–inhibitory neuronal assemblages are fundamental objectives in the study of the nervous system. They are recognized in all strata of the motor cortex. Most local-circuit interneurons recognized in the motor cortex are inhibitory in nature. Because, pyramidal cells represent roughly the 70% and the local-circuit interneurons the 30% of the motor cortex gray matter neurons, each inhibitory neuron establishes synaptic contacts with numerous pyramidal neurons. The excitatory pyramidal neurons are morphologically stable and functionally anchored to the first lamina. On the other hand, the inhibitory neurons are free, without first lamina attachment, capable of modifying their dendritic and axonic profiles as well as their spatial distribution in response to learned (acquired) new motor activities.

The Hindmarsh-Rose (HR) model could describe different discharge property of an excitatory or inhibitory neuron by changing the parameter r . In this paper, HR model is used to be the dynamical equations of the spiking model neurons, and different neurons in one neuronal population are connected with WS small-world network. A neurons spiking model in the hippocampus CA3 based on small-world network is established on the Matlab platform. Spike trains of the neurons spiking model are simulated when no stimulus and a pulse current acted on the model. Then rate coding and synchrony coding are used to analysis the simulated spiking trains. Experiment results indicate when no stimulus acts on the neurons spike model, the spike firing of hippocampus CA3 is sparse. When a stimulus acts on the neurons spike model, the mean population firing rate increased obviously. The increasing of neurons firing rate could present the ensemble activities, which highly correlate with memory.

In this paper, we propose a simple supervised associative learning approach for spiking neural networks. In an excitatory-inhibitory network paradigm with Izhikevich spiking neurons, synaptic plasticity is implemented on excitatory to excitatory synapses dependent on both spike emission rates and spike timings. As results of learning, the network is able to associate not just familiar stimuli but also novel stimuli observed through synchronised activity within the same subpopulation and between two associated subpopulations.

We investigated the network topology organized through spike-timingdependent plasticity (STDP) using pair- and triad-connectivity patterns, considering difference of excitatory and inhibitory neurons. As a result, we found that inhibitory synaptic strength affects statistical properties of the network topology organized through STDP more strongly than the bias of the external input rate for the excitatory neurons. In addition, we also found that STDP leads highly nonrandom structure to the neural network. Our analysis from a viewpoint of connectivity pattern transitions reveals that STDP does not uniformly strengthen and depress excitatory synapses in neural networks. Further, we also found that the significance of triad-connectivity patterns after the learning results from the fact that the probability of triad-connectivity-pattern transitions is much higher than that of combinations of pair-connectivity-pattern transitions.

Spike response was investigated in 104 neurons of the nucleus reticularis thalami (R) and adjoining thalamic nuclei to acoustic, tactile, and visual stimuli during chronic experiments on cats. Of the test neurons, 29% responded to acoustic stimulation and 11% showed no preference in relation to different acoustic stimuli. Minimum latencies of response to sounds measured 12–37 msec in excitatory and 18–27 msec in inhibitory cells. Duration of excitation produced by acoustic stimuli reached 50–250 msec; inhibition lasted 27–190 msec. Most cells belonging to this nucleus were excited by different stimuli; the proportion of inhibitory neurons did not exceed 4–10%.

Regularly spiking neurons are classified into two categories, Class I and Class II, by their firing properties for constant inputs. To investigate how the firing properties of single neurons affect to ensemble rhythmic activities in neural networks, we constructed different types of neural networks whose excitatory neurons are the Class I neurons or the Class II neurons. The networks were driven by random inputs and developed with STDP learning. As a result, the Class I and the Class II neural networks generate different types of rhythmic activities: the Class I neural network generates slow rhythmic activities, and the Class II neural network generates fast rhythmic activities.

Summary form only given. In our simulations of hippocampal region CA3, we have observed a variety of dynamical behaviors over the course of learning. Such dynamics can either help or hurt the model as it is being trained to learn a cognitive task that depends on normal hippocampal function. The parameterization of the time spanning, associative synaptic modification rule has been investigated. In particular there is an interaction between the time constant of the NMDA-receptor and input longevity that has a direct effect on the dynamics of the neuronal codes that form. Inhibition potently affects the dynamics of cell firing, and it is easy to lose activity control when the excitatory synapses between primary, excitatory neurons alone are being modified. Synaptic modification of either the input or output synapses of an inhibitory neuron can, to a greater or lesser extent, compensate for synaptic modifications between primary neurons.

Some synapses between cortical pyramidal neurons exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes. Since depressing synapses do not transmit information on sustained presynaptic firing rates, it has been speculated that they are favorable for temporal coding. In this paper, we study the dynamical effects of depressing synapses on stimulus-induced transient synchronization in a simple network of inhibitory interneurons and excitatory neurons, assuming that the recurrent excitation is mediated by depressing synapses. This synchronization occurs in a temporal pattern which depends on a given stimulus. Since the presence of noise is always a potential hazard in temporal coding, we investigate the extent to which noise in stimuli influences the synchronization phenomena. It is demonstrated that depressing synapses greatly contribute to suppressing the influences of noise on the stimulus-specific temporal patterns of synchronous firing. The timing-based Hebbian learning revealed by physiological experiments is shown to stabilize the temporal patterns in cooperation with synaptic depression. Thus, the times at which synchronous firing occurs provides a reliable information representation in the presence of synaptic depression.

A network of integrate-and-fire units (consisting of five excitatory units and one inhibitory unit) is shown to implement a one dimensional frequency map over one octave (80 – 160Hz). The network has a biologically plausible structure, conforming to Dale’s law, and using plausible synaptic and axonic timings.

The CI neurons innervating the leg muscles in crabs are mainly tonically active during walking. They suppress synaptic excitation predominantly in the tonic fibers in all leg muscles. This facilitates rapid contraction and relaxation cycles of the limb muscles. Whereas specific inhibitors exert inhibition only when their activity is closely coupled to the discharge of the excitatory neuron, the effects of CI neurons persist over a longer period. This guarantees effective presynaptic inhibition of excitatory transmitter release without tight coupling of CI to excitatory discharges. It explains the effective inhibition exerted by a single CI neuron on a large number of muscles located in different j oints of the leg, some of which are coactivated during walking.

Electrical responses of 25 presumptive hippocampal inhibitory interneurons to stimulation of two afferent systems of fibers, originating in the contralateral hippocampus, were investigated in acute experiments on unanesthetized, immobilized rabbits. Inhibitory neurons were found to have a relatively ineffective inhibitory input as well as a very effective excitatory input. On interaction between synaptic processes during spontaneous and evoked activity the excitatory input clearly predominates over the inhibitory and plays a definite role in behavior of the neurons.

Postural reflexes act through a single excitatory motoneuron of the several that innervate a flexor muscle of the cockroach leg. A peripheral inhibitory neuron whose axon accompanies this excitatory motoneuron is able to suppress muscle tensions developed from postural reflexes without affecting centrally generated muscle tensions. The inhibitory neuron could thus serve to rapidly suppress postural tensions at the initiation of escape.

1. Investigations on a mathematical model have shown that the presence of an optimal system of parameters of neuron-like excitatory elements (EE) and of connections between them is essential for the undistorted conduction of excitation along a network composed of them. If these parameters deviate from their optimal values excitation will be transmitted along the net either with attenuation or with amplification, due to the presence of divergence and convergence of influences of EE of the preceding layer of the net on the succeeding layer. 2. Optimal values of the parameters of EE and of the connections between them for undistorted conduction of excitation are not strictly determined. Deviations of some parameters can be compensated by changes in others. 3. The presence of dispersion of thresholds of EE induces chaos in the working of the net, weakens the degree of synchronization in the activation of EE to an external agency, and impairs the detection of activity of input EE at the output of the net. 4. Background activity of the net, both tonic and periodic, above the threshold for impulse generation prevents the appearance of activation of input EE at the output of the net, whereas near-threshold tonic activity of the net facilitates the conduction of excitation along it. 5. Periodic below-threshold activity of the net facilitates the conduction of excitation along it only in the presence of optimal proportions of frequencies and phase shift of coherent rhythmic oscillations of excitability of EE, and also of the time required for excitation to be transmitted from the input of the net to its output. If those conditions are not present, the presence of below-threshold rhythmic oscillations of excitability (including high-frequency oscillations) in the net will limit the conduction of excitation along it by comparison with tonic below-threshold activation.

The reverberation that occurs between two neuron groups, which have excitatory mono-synaptic random connections with each other can be studied theoretically by employing a model neuron, which expresses well the characters of a real neuron. In this model we consider three effects, which are; the effect of the summation of the excitatory post-synaptic potential (EPSP) of neurons; the effect of the spontaneous firing of neurons as a noise in groups and the effect of the relative refractory period of neurons. As a result, it is shown that under the effect of the summation of the EPSP of neurons and the effect of the noise, the systematic threshold p ϑ takes the same value as is observed in practice. The effect of the relative refractory period has been considered in order to explain the low speed of the increase in firing activity, as observed in the reverberating system. It suppresses slightly the speed of the increase in firing activity ( p i ) in the system. Moreover, the speed can be suppressed by making the refractory effect strong according to the increase of p i . However, the initial increase of p i at a high speed that was observed in the experiment cannot be explained simply by the effect of the refractoriness, even if it were the absolute refractoriness.

Nervous systems cannot adequately be described as randomly connected networks consisting of excitatory and inhibitory neurons, because neuron populations and even single neurons show highly diverse connectivities. Many neuron populations never get a chance to form synaptic connections with each other, while for other neurons the probability of forming synapses with other neurons rises continously during ontogenesis.

The network was a randomly connected network of excitatory and inhibitory neurons, that can exhibit both asynchronous and synchronous irregular activity, in which the global activity oscillates in time with a frequency that depends both on synaptic time constants and on the excitation/inhibition balance [1]. The LFP was modeled as a linear combination of excitatory and inhibitory currents. This choice allows us to reproduce the dependence of the LFP spectrum on frequency and contrast as recorded in vivo [2].