Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex

Canonical Organization of Layer 1 Neuron-Led Cortical Inhibitory and Disinhibitory Interneuronal Circuits

Interneurons play a key role in cortical function and dysfunction, yet organization of cortical interneuronal circuitry remains poorly understood. Cortical Layer 1 (L1) contains 2 general GABAergic interneuron groups, namely single bouquet cells (SBCs) and elongated neurogliaform cells (ENGCs). SBCs predominantly make unidirectional inhibitory connections (SBC→) with L2/3 interneurons, whereas ENGCs frequently form reciprocal inhibitory and electric connections (ENGC↔) with L2/3 interneurons. Here, we describe a systematic investigation of the pyramidal neuron targets of L1 neuron-led interneuronal circuits in the rat barrel cortex with simultaneous octuple whole-cell recordings and report a simple organizational scheme of the interneuronal circuits. Both SBCs→ and ENGC ↔ L2/3 interneuronal circuits connect to L2/3 and L5, but not L6, pyramidal neurons. SBC → L2/3 interneuronal circuits primarily inhibit the entire dendritic-somato-axonal axis of a few L2/3 and L5 pyramidal neurons located within the same column. In contrast, ENGC ↔ L2/3 interneuronal circuits generally inhibit the distal apical dendrite of many L2/3 and L5 pyramidal neurons across multiple columns. Finally, L1 interneuron-led circuits target distinct subcellular compartments of L2/3 and L5 pyramidal neurons in a L2/3 interneuron type-dependent manner. These results suggest that L1 neurons form canonical interneuronal circuits to control information processes in both supra- and infragranular cortical layers.

Input statistics and Hebbian cross-talk effects

As an extension of prior work, we studied inspecific Hebbian learning using the classical Oja model. We used a combination of analytical tools and numerical simulations to investigate how the effects of synaptic cross talk (which we also refer to as synaptic inspecificity) depend on the input statistics. We investigated a variety of patterns that appear in dimensions higher than two (and classified them based on covariance type and input bias). We found that the effects of cross talk on learning dynamics and outcome is highly dependent on the input statistics and that cross talk may lead in some cases to catastrophic effects on learning or development. Arbitrarily small levels of cross talk are able to trigger bifurcations in learning dynamics, or bring the system in close enough proximity to a critical state, to make the effects indistinguishable from a real bifurcation. We also investigated how cross talk behaves toward unbiased ("competitive") inputs and in which circumstances it can help the system productively resolve the competition. Finally, we discuss the idea that sophisticated neocortical learning requires accurate synaptic updates (similar to polynucleotide copying, which requires highly accurate replication). Since it is unlikely that the brain can completely eliminate cross talk, we support the proposal that is uses a neural mechanism that "proofreads" the accuracy of the updates, much as DNA proofreading lowers copying error rate.

Recurrent synapses and circuits in the CA3 region of the hippocampus: an associative network

In the CA3 region of the hippocampus, pyramidal cells excite other pyramidal cells and interneurons. The axons of CA3 pyramidal cells spread throughout most of the region to form an associative network. These connections were first drawn by Cajal and Lorente de No. Their physiological properties were explored to understand epileptiform discharges generated in the region. Synapses between pairs of pyramidal cells involve one or few release sites and are weaker than connections made by mossy fibers on CA3 pyramidal cells. Synapses with interneurons are rather effective, as needed to control unchecked excitation. We examine contributions of recurrent synapses to epileptiform synchrony, to the genesis of sharp waves in the CA3 region and to population oscillations at theta and gamma frequencies. Recurrent connections in CA3, as other associative cortices, have a lower connectivity spread over a larger area than in primary sensory cortices. This sparse, but wide-ranging connectivity serves the functions of an associative network, including acquisition of neuronal representations as activity in groups of CA3 cells and completion involving the recall from partial cues of these ensemble firing patterns.

Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration

Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the offline, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This Perspective considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity.

Reliable neuronal systems: the importance of heterogeneity

For every engineer it goes without saying: in order to build a reliable system we need components that consistently behave precisely as they should. It is also well known that neurons, the building blocks of brains, do not satisfy this constraint. Even neurons of the same type come with huge variances in their properties and these properties also vary over time. Synapses, the connections between neurons, are highly unreliable in forwarding signals. In this paper we argue that both these fact add variance to neuronal processes, and that this variance is not a handicap of neural systems, but that instead predictable and reliable functional behavior of neural systems depends crucially on this variability. In particular, we show that higher variance allows a recurrently connected neural population to react more sensitively to incoming signals, and processes them faster and more energy efficient. This, for example, challenges the general assumption that the intrinsic variability of neurons in the brain is a defect that has to be overcome by synaptic plasticity in the process of learning.

Mapping mammalian synaptic connectivity

Mapping mammalian synaptic connectivity has long been an important goal of neuroscientists since it is considered crucial for explaining human perception and behavior. Yet, despite enormous efforts, the overwhelming complexity of the neural circuitry and the lack of appropriate techniques to unravel it have limited the success of efforts to map connectivity. However, recent technological advances designed to overcome the limitations of conventional methods for connectivity mapping may bring about a turning point. Here, we address the promises and pitfalls of these new mapping technologies.

High concentrations of divalent cations isolate monosynaptic inputs from local circuits in the auditory midbrain

Hierarchical processing of sensory information occurs at multiple levels between the peripheral and central pathway. Different extents of convergence and divergence in top down and bottom up projections makes it difficult to separate the various components activated by a sensory input. In particular, hierarchical processing at sub-cortical levels is little understood. Here we have developed a method to isolate extrinsic inputs to the inferior colliculus (IC), a nucleus in the midbrain region of the auditory system, with extensive ascending and descending convergence. By applying a high concentration of divalent cations (HiDi) locally within the IC, we isolate a HiDi-sensitive from a HiDi-insensitive component of responses evoked by afferent input in brain slices and in vivo during a sound stimulus. Our results suggest that the HiDi-sensitive component is a monosynaptic input to the IC, while the HiDi-insensitive component is a local polysynaptic circuit. Monosynaptic inputs have short latencies, rapid rise times, and underlie first spike latencies. Local inputs have variable delays and evoke long-lasting excitation. In vivo, local circuits have variable onset times and temporal profiles. Our results suggest that high concentrations of divalent cations should prove to be a widely useful method of isolating extrinsic monosynaptic inputs from local circuits in vivo.

Contribution of intracolumnar layer 2/3-to-layer 2/3 excitatory connections in shaping the response to whisker deflection in rat barrel cortex

This computational study integrates anatomical and physiological data to assess the functional role of the lateral excitatory connections between layer 2/3 (L2/3) pyramidal cells (PCs) in shaping their response during early stages of intracortical processing of a whisker deflection (WD). Based on in vivo and in vitro recordings, and 3D reconstructions of connected pairs of L2/3 PCs, our model predicts that: 1) AMPAR and NMDAR conductances/synapse are 0.52 ± 0.24 and 0.40 ± 0.34 nS, respectively; 2) following WD, connection between L2/3 PCs induces a composite EPSPs of 7.6 ± 1.7 mV, well below the threshold for action potential (AP) initiation; 3) together with the excitatory feedforward L4-to-L2/3 connection, WD evoked a composite EPSP of 16.3 ± 3.5 mV and a probability of 0.01 to generate an AP. When considering the variability in L4 spiny neurons responsiveness, it increased to 17.8 ± 11.2 mV; this 3-fold increase in the SD yielded AP probability of 0.35; 4) the interaction between L4-to-L2/3 and L2/3-to-L2/3 inputs is highly nonlinear; 5) L2/3 dendritic morphology significantly affects L2/3 PCs responsiveness. We conclude that early stages of intracortical signaling of WD are dominated by a combination of feedforward L4-L2/3 and L2/3-L2/3 lateral connections.

The influence of synaptic weight distribution on neuronal population dynamics

The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.

Induction and modulation of persistent activity in a layer V PFC microcircuit model

Working memory refers to the temporary storage of information and is strongly associated with the prefrontal cortex (PFC). Persistent activity of cortical neurons, namely the activity that persists beyond the stimulus presentation, is considered the cellular correlate of working memory. Although past studies suggested that this type of activity is characteristic of large scale networks, recent experimental evidence imply that small, tightly interconnected clusters of neurons in the cortex may support similar functionalities. However, very little is known about the biophysical mechanisms giving rise to persistent activity in small-sized microcircuits in the PFC. Here, we present a detailed biophysically—yet morphologically simplified—microcircuit model of layer V PFC neurons that incorporates connectivity constraints and is validated against a multitude of experimental data. We show that (a) a small-sized network can exhibit persistent activity under realistic stimulus conditions. (b) Its emergence depends strongly on the interplay of dADP, NMDA, and GABA_B currents. (c) Although increases in stimulus duration increase the probability of persistent activity induction, variability in the stimulus firing frequency does not consistently influence it. (d) Modulation of ionic conductances (I_h, I_D, I_sAHP, I_caL, I_caN, I_caR) differentially controls persistent activity properties in a location dependent manner. These findings suggest that modulation of the microcircuit's firing characteristics is achieved primarily through changes in its intrinsic mechanism makeup, supporting the hypothesis of multiple bi-stable units in the PFC. Overall, the model generates a number of experimentally testable predictions that may lead to a better understanding of the biophysical mechanisms of persistent activity induction and modulation in the PFC.

Age dependency of trauma-induced neocortical epileptogenesis

Trauma and brain infection are the primary sources of acquired epilepsy, which can occur at any age and may account for a high incidence of epilepsy in developing countries. We have explored the hypothesis that penetrating cortical wounds cause deafferentation of the neocortex, which triggers homeostatic plasticity and lead to epileptogenesis (Houweling etal., 2005). In partial deafferentation experiments of adult cats, acute seizures occurred in most preparations and chronic seizures occurred weeks to months after the operation in 65% of the animals (Nita etal., 2006,2007; Nita and Timofeev, 2007). Similar deafferentation of young cats (age 8-12 months) led to some acute seizures, but we never observed chronic seizure activity even though there was enhanced slow-wave activity in the partially deafferented hemisphere during quiet wakefulness. This suggests that despite a major trauma, the homeostatic plasticity in young animals was able to restore normal levels of cortical excitability, but in fully adult cats the mechanisms underlying homeostatic plasticity may lead to an unstable cortical state. To test this hypothesis we made an undercut in the cortex of an elderly cat. After several weeks this animal developed seizure activity. These observations may lead to an intervention after brain trauma that prevents epileptogenesis from occurring in adults.

Detection of submillisecond spike timing differences based on delay-line anticoincidence detection

Detection of submillisecond interaural timing differences is the basis for sound localization in reptiles, birds, and mammals. Although comparative studies reveal that different neural circuits underlie this ability, they also highlight common solutions to an inherent challenge: processing information on timescales shorter than an action potential. Discrimination of small timing differences is also important for species recognition during communication among mormyrid electric fishes. These fishes generate a species-specific electric organ discharge (EOD) that is encoded into submillisecond-to-millisecond timing differences between receptors. Small, adendritic neurons (small cells) in the midbrain are thought to analyze EOD waveform by comparing these differences in spike timing, but direct recordings from small cells have been technically challenging. In the present study we use a fluorescent labeling technique to obtain visually guided extracellular recordings from individual small cell axons. We demonstrate that small cells receive 1-2 excitatory inputs from 1 or more receptive fields with latencies that vary by over 10 ms. This wide range of excitatory latencies is likely due to axonal delay lines, as suggested by a previous anatomic study. We also show that inhibition of small cells from a calyx synapse shapes stimulus responses in two ways: through tonic inhibition that reduces spontaneous activity and through precisely timed, stimulus-driven, feed-forward inhibition. Our results reveal a novel delay-line anticoincidence detection mechanism for processing submillisecond timing differences, in which excitatory delay lines and precisely timed inhibition convert a temporal code into a population code.

Connectomic reconstruction of the inner plexiform layer in the mouse retina

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer--the main computational neuropil region in the mammalian retina--the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.

Effects of repeated stress on excitatory drive of basal amygdala neurons in vivo

Chronic stress leads to heightened affective behaviors, and can precipitate the emergence of depression and anxiety. These disorders are associated with increased amygdala activity. In animal models, chronic stress leads to increased amygdala-dependent behaviors, as well as hyperactivity of amygdala neurons. However, it is not known whether increased excitatory synaptic drive after chronic stress contributes to hyperactivity of basolateral amygdala (BLA; comprised of basal, lateral, and accessory basal nuclei) neurons. This study tested whether repeated stress causes an increase in excitatory drive of basal amygdala (BA) neurons in vivo, and whether this is correlated with an increase in the number of dendritic spines and a shift in dendritic distribution. Using in vivo intracellular recordings, this study found that repeated restraint stress caused an increase in the frequency of spontaneous excitatory synaptic events in vivo, which correlated with the number of dendritic spines in reconstructed neurons. Furthermore, parallel changes in the kinetics of the synaptic events and the distribution of spines indicated a more prominent functional contribution of synaptic inputs from across the dendritic tree. The shift in spine distribution across the dendritic tree was further confirmed with the examination of Golgi-stained tissue. This abnormal physiological drive of BA neurons after repeated stress may contribute to heightened affective responses after chronic stress. A reduction in the impact of excitatory drive in the BA may therefore be a potential treatment for the harmful effects of chronic stress in psychiatric disorders.

Fear signaling in the prelimbic-amygdala circuit: a computational modeling and recording study

The acquisition and expression of conditioned fear depends on prefrontal-amygdala circuits. Auditory fear conditioning increases the tone responses of lateral amygdala neurons, but the increase is transient, lasting only a few hundred milliseconds after tone onset. It was recently reported that that the prelimbic (PL) prefrontal cortex transforms transient lateral amygdala input into a sustained PL output, which could drive fear responses via projections to the lateral division of basal amygdala (BL). To explore the possible mechanisms involved in this transformation, we developed a large-scale biophysical model of the BL-PL network, consisting of 850 conductance-based Hodgkin-Huxley-type cells, calcium-based learning, and neuromodulator effects. The model predicts that sustained firing in PL can be derived from BL-induced release of dopamine and norepinephrine that is maintained by PL-BL interconnections. These predictions were confirmed with physiological recordings from PL neurons during fear conditioning with the selective β-blocker propranolol and by inactivation of BL with muscimol. Our model suggests that PL has a higher bandwidth than BL, due to PL's decreased internal inhibition and lower spiking thresholds. It also suggests that variations in specific microcircuits in the PL-BL interconnection can have a significant impact on the expression of fear, possibly explaining individual variability in fear responses. The human homolog of PL could thus be an effective target for anxiety disorders.

Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system

Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

Probabilistic inference of short-term synaptic plasticity in neocortical microcircuits

Short-term synaptic plasticity is highly diverse across brain area, cortical layer, cell type, and developmental stage. Since short-term plasticity (STP) strongly shapes neural dynamics, this diversity suggests a specific and essential role in neural information processing. Therefore, a correct characterization of short-term synaptic plasticity is an important step towards understanding and modeling neural systems. Phenomenological models have been developed, but they are usually fitted to experimental data using least-mean-square methods. We demonstrate that for typical synaptic dynamics such fitting may give unreliable results. As a solution, we introduce a Bayesian formulation, which yields the posterior distribution over the model parameters given the data. First, we show that common STP protocols yield broad distributions over some model parameters. Using our result we propose a experimental protocol to more accurately determine synaptic dynamics parameters. Next, we infer the model parameters using experimental data from three different neocortical excitatory connection types. This reveals connection-specific distributions, which we use to classify synaptic dynamics. Our approach to demarcate connection-specific synaptic dynamics is an important improvement on the state of the art and reveals novel features from existing data.

Matched pre- and post-synaptic changes underlie synaptic plasticity over long time scales

Modifications of synaptic efficacies are considered essential for learning and memory. However, it is not known how the underlying functional components of synaptic transmission change over long time scales. To address this question, we studied cortical synapses from young Wistar rats before and after 12 h intervals of spontaneous or glutamate-induced spiking activity. We found that, under these conditions, synaptic efficacies can increase or decrease by up to 10-fold. Statistical analyses reveal that these changes reflect modifications in the number of presynaptic release sites, together with postsynaptic changes that maintain the quantal size per release site. The quantitative relation between the presynaptic and postsynaptic transmission components was not affected when synaptic plasticity was enhanced or reduced using a broad range of pharmacological agents. These findings suggest that ongoing synaptic plasticity results in matched presynaptic and postsynaptic modifications, in which elementary modules that span the synaptic cleft are added or removed as a function of experience.

Nonuniform distribution of contacts from noradrenergic and serotonergic boutons on the dendrites of cat splenius motoneurons

The input-output properties of motoneurons are dynamically regulated. This regulation depends, in part, on the relative location of excitatory and inhibitory synapses, voltage-dependent and -independent channels, and neuromodulatory synapses on the dendritic tree. The goal of the present study was to quantify the number and distribution of synapses from two powerful neuromodulatory systems that originate from noradrenergic (NA) and serotonergic (5-HT) neurons. Here we show that the dendritic trees of motoneurons innervating a dorsal neck extensor muscle, splenius, in the adult cat are densely, but not uniformly innervated by both NA and 5-HT boutons. Identified splenius motoneurons were intracellularly stained with Neurobiotin. Using 3D reconstruction techniques we mapped the distributions of contacts formed by NA and 5-HT boutons on the reconstructed dendritic trees of these motoneurons. Splenius motoneurons received an average of 1,230 NA contacts (range = 647-1,507) and 1,582 5-HT contacts (range = 1,234-2,143). The densities of these contacts were 10 (NA) to 6 (5-HT)-fold higher on small compared to large-diameter dendrites. This relationship largely accounts for the bias of NA and 5-HT contacts on distal dendrites and is partially responsible for the higher density of NA contacts on dendrites located more than 200 μm dorsal to the soma. These results suggest that the neuromodulatory actions of NA and 5-HT are compartmentalized and regulate the input-output properties of motoneurons according to precisely arranged interactions with voltage-dependent and -independent channels that are primarily located on small-diameter dendrites.

Synaptic mechanisms underlying functional dichotomy between intrinsic-bursting and regular-spiking neurons in auditory cortical layer 5

Corticofugal projections from the primary auditory cortex (A1) have been shown to play a role in modulating subcortical processing. However, functional properties of the corticofugal neurons and their synaptic circuitry mechanisms remain unclear. In this study, we performed in vivo whole-cell recordings from layer 5 (L5) pyramidal neurons in the rat A1 and found two distinct neuronal classes according to their functional properties. Intrinsic-bursting (IB) neurons, the L5 corticofugal neurons, exhibited early and rather unselective spike responses to a wide range of frequencies. The exceptionally broad spectral tuning of IB neurons was attributable to their broad excitatory inputs with long temporal durations and inhibitory inputs being more narrowly tuned than excitatory inputs. This uncommon pattern of excitatory-inhibitory interplay was attributed initially to a broad thalamocortical convergence onto IB neurons, which also receive temporally prolonged intracortical excitatory input as well as feedforward inhibitory input at least partially from more narrowly tuned fast-spiking inhibitory neurons. In contrast, regular-spiking neurons, which are mainly corticocortical, exhibited sharp frequency tuning similar to L4 pyramidal cells, underlying which are well-matched purely intracortical excitation and inhibition. The functional dichotomy among L5 pyramidal neurons suggests two distinct processing streams. The spectrally and temporally broad synaptic integration in IB neurons may ensure robust feedback signals to facilitate subcortical function and plasticity in a general manner.

The influence of phospho-τ on dendritic spines of cortical pyramidal neurons in patients with Alzheimer's disease

The dendritic spines on pyramidal cells represent the main postsynaptic elements of cortical excitatory synapses and they are fundamental structures in memory, learning and cognition. In the present study, we used intracellular injections of Lucifer yellow in fixed tissue to analyse over 19 500 dendritic spines that were completely reconstructed in three dimensions along the length of the basal dendrites of pyramidal neurons in the parahippocampal cortex and CA1 of patients with Alzheimer’s disease. Following intracellular injection, sections were immunostained for anti-Lucifer yellow and with tau monoclonal antibodies AT8 and PHF-1, which recognize tau phosphorylated at Ser202/Thr205 and at Ser396/404, respectively. We observed that the diffuse accumulation of phospho-tau in a putative pre-tangle state did not induce changes in the dendrites of pyramidal neurons, whereas the presence of tau aggregates forming intraneuronal neurofibrillary tangles was associated with progressive alteration of dendritic spines (loss of dendritic spines and changes in their morphology) and dendrite atrophy, depending on the degree of tangle development. Thus, the presence of phospho-tau in neurons does not necessarily mean that they suffer severe and irreversible effects as thought previously but rather, the characteristic cognitive impairment in Alzheimer’s disease is likely to depend on the relative number of neurons that have well developed tangles.

Repeated restraint stress exerts different impact on structure of neurons in the lateral and basal nuclei of the amygdala

Chronic stress exacerbates and can induce symptoms of depression and anxiety disorders. Chronic stress causes amygdala hyperactivity, which may contribute to these detrimental effects. One potential mechanism for amygdala hyperactivity is an increase of excitatory drive after stress. Excitatory inputs to the amygdala predominantly synapse upon dendritic spines, and repeated stress has been demonstrated to increase dendritic spines in the basolateral amygdala (BLA). However, the BLA is comprised of several nuclei, including the lateral nucleus (LAT) and the basal nucleus (BA), which exert functionally distinct roles in amygdala-dependent behaviors. Furthermore, while an increase of dendritic spines can impart significant functional ramifications, a shift of spine distribution can also exert significant impact. However, differences in the effects of repeated stress on LAT and BA have not been examined, nor differential effects on spine distribution. This study examined the effects of repeated restraint stress on dendritic structure of principal neurons from the LAT and BA in Golgi-stained tissue. This study found that repeated stress increased spine number in LAT and BA, but in very distinct patterns, with proximal increases in LAT neurons and non-proximal increases in BA neurons. Furthermore, repeated stress increased dendritic length in the BA, but not the LAT, leading to a global change of spine density in BA, but a focal change in LAT. These distinct effects of repeated stress in the LAT and BA may exert significant functional effects on fear behavior, and may underlie differences in the effects of repeated stress on acquisition, contextual modulation and extinction of fear behavior.

Adenosine A1 receptor activation mediates the developmental shift at layer 5 pyramidal cell synapses and is a determinant of mature synaptic strength

During the first postnatal month glutamatergic synapses between layer 5 pyramidal cells in the rodent neocortex switch from an immature state exhibiting a high probability of neurotransmitter release, large unitary amplitude and synaptic depression to a mature state with decreased probability of release, smaller unitary amplitude and synaptic facilitation. Using paired recordings, we demonstrate that the developmental shift in release probability at synapses between rat somatosensory layer 5 thick-tufted pyramidal cells is mediated by a higher and more heterogeneous activation of presynaptic adenosine A₁ receptors. Immature synapses under control conditions exhibited distributions of coefficient of variation, failure rate and release probability that were almost coincident with the A₁ receptor blocked condition; however, mature synapses under control conditions exhibited much broader distributions that spanned those of both the A₁ receptor agonized and antagonized conditions. Immature and mature synapses expressed A₁ receptors with no observable difference in functional efficacy and therefore the heterogeneous A₁ receptor activation seen in the mature neocortex appears due to increased adenosine concentrations that vary between synapses. Given the central role demonstrated for A₁ receptor activation in determining synaptic amplitude and the statistics of transmission between mature layer 5 pyramidal cells, the emplacement of adenosine sources and sinks near the synaptic terminal could constitute a novel form of long-term synaptic plasticity.

Metastability and inter-band frequency modulation in networks of oscillating spiking neuron populations

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain.

Silent synapses persist into adulthood in layer 2/3 pyramidal neurons of visual cortex in dark-reared mice

Immature excitatory synapses often have NMDA receptors but not AMPA receptors in central neurons, including visual cortical pyramidal neurons. These synapses, called silent synapses, are converted to functional synapses with AMPA receptors by NMDA receptor activation during early development. It is likely that this process underlies the activity-dependent refinement of neuronal circuits and brain functions. In the present study, we investigated postnatal development of excitatory synapses, focusing on the role of visual inputs in the conversion of silent to functional synapses in mouse visual cortex. We analyzed presumably unitary excitatory postsynaptic currents (EPSCs) between a pair of layer 2/3 pyramidal neurons, using minimal stimulation with a patch pipette attached to the soma of one of the pair. The proportion of silent synapses was estimated by the difference in the failure rate between AMPA- and NMDA-EPSCs. In normal development, silent synapses were present abundantly before eye opening, decreased considerably by the critical period of ocular dominance plasticity, and almost absent in adulthood. This decline in silent synapses was prevented by dark rearing. The amplitude of presumably unitary AMPA-EPSCs increased with age, but this increase was suppressed by dark rearing. The quantal amplitude of AMPA-EPSCs and paired-pulse ratio of NMDA-EPSCs both remained unchanged during development, independent of visual experience. These results indicate that visual inputs are required for the conversion of silent to functional synapses and this conversion largely contributes to developmental increases in the amplitude of presumably unitary AMPA-EPSCs.

A target cell-specific role for presynaptic Fmr1 in regulating glutamate release onto neocortical fast-spiking inhibitory neurons

In the mouse model of Fragile X syndrome, the Fmr1 knock-out, local excitation of layer 4 fast-spiking (FS) inhibitory neurons is robustly decreased by 50%, but the mechanisms mediating this change are unknown. Here, we performed recordings in acutely prepared slices obtained from Fmr1 "mosaic" mice, where Fmr1 is deleted in about half of all neurons, and we found that loss of presynaptic, but not postsynaptic, Fmr1 fully recapitulates the deficit. The change in connection strength is primarily due to a decrease in release probability indicating that FMRP normally positively regulates these processes. This change in presynaptic neurotransmitter release is observed both in the mosaic mice and in the constitutive Fmr1 knock-out mice. Manipulations in release probability enabled both the mimic and rescue of the impaired function in this synaptic pathway. Loss of presynaptic Fmr1 has no effect on excitatory synapses onto excitatory neurons, indicating a target cell-specific function for presynaptic FMRP. Finally, we demonstrate that the excitation decrement onto FS neurons also exists in layer 5 of the Fmr1 knock-out, suggesting a widespread role for presynaptic Fmr1 in the excitation of inhibitory neurons. In summary, we identify a novel function for presynaptic FMRP in promoting presynaptic neurotransmitter release, and we show that loss of this function accounts for impaired excitation of neocortical FS inhibitory neurons. These changes may contribute to the cognitive dysfunction and circuit hyperexcitability associated with Fragile X syndrome, including patients with complete deletion of FMRP and those with mosaic expression of FMRP.

Neuronal damage and gliosis in the somatosensory cortex induced by various durations of transient cerebral ischemia in gerbils

Although many studies regarding ischemic brain damage in the gerbil have been reported, studies on neuronal damage according to various durations of ischemia-reperfusion (I-R) have been limited. In this study, we examined neuronal damage/death and glial changes in the somatosensory cortex 4 days after 5, 10 and 15 min of transient cerebral ischemia using the gerbil. To examine neuronal damage, we used Fluoro-Jade B (F-J B, a marker for neuronal degeneration) histofluorescence staining as well as cresyl violet (CV) staining and neuronal nuclei (NeuN, neuronal marker) immunohistochemistry. In the somatosensory cortex, some CV and NeuN positive (+) neurons were slightly decreased only in layers III and VI in the 5 min ischemia-group, and the number of CV+ and NeuN+ neurons were decreased with longer ischemic time. The F-J B histofluorescence staining showed a clear neuronal damage in layers III and VI, and the number of F-J B+ neurons was increased with time of ischemia-reperfusion: in the 15 min ischemia-group, the number of F-J B+ neurons was much higher in layer III than in layer VI. In addition, we immunohistochemically examined gliosis of astrocytes and microglia using anti-glial fibrillary acidic protein (GFAP) and anti-ionized calcium-binding adapter molecule 1 (Iba-1) antibody, respectively. In the 5 min ischemia-group, GFAP+ astrocytes and Iba-1+ microglia were distinctively increased in number, and their immunoreactivity was stronger than that in the sham-group. In the 10 and 15 min ischemia-groups, numbers of GFAP+ and Iba-1+ glial cells were much more increased with time of ischemia-reperfusion; in the 15 min ischemia-group, their distribution patterns of GFAP+ and Iba-1+ glial cells were similar to those in the 10 min ischemia-group. Our fining indicates that neuronal death/damage and gliosis of astrocytes and microglia were apparently increased with longer time of ischemia-reperfusion.

Target selectivity of feedforward inhibition by striatal fast-spiking interneurons

The striatal microcircuitry consists of a vast majority of projection neurons, the medium spiny neurons (MSNs), and a small yet diverse population of interneurons. To understand how activity is orchestrated within the striatum, it is essential to unravel the functional connectivity between the different neuronal types. Fast-spiking (FS) interneurons provide feedforward inhibition to both direct and indirect pathway MSNs and are important in sculpting their output to downstream basal ganglia nuclei. FS interneurons are also interconnected with each other via electrical and chemical synapses; however, whether and how they inhibit other striatal interneuron types remains unknown. In this study we combined multineuron whole-cell recordings with optogenetics to determine the target selectivity of feedforward inhibition by striatal FS interneurons. Using transgenic and viral approaches we directed expression of channelrhodopsin 2 (ChR2) to FS interneurons to study their connectivity within the mouse striatal microcircuit. Optogenetic stimulation of ChR2-expressing FS interneurons generated strong and reliable GABA(A)-dependent synaptic inputs in MSNs. In sharp contrast, simultaneously recorded neighboring cholinergic interneurons did not receive any synaptic inputs from photostimulated FS cells, and a minority of low-threshold spiking (LTS) interneurons responded weakly. We further tested the synaptic connectivity between FS and LTS interneurons using paired recordings, which showed only sparse connectivity. Our results show that striatal FS interneurons form a feedforward inhibitory circuit that is target selective, inhibiting projection neurons while avoiding cholinergic interneurons and sparsely contacting LTS interneurons, thus supporting independent modulation of MSN activity by the different types of striatal interneurons.

Neuronal morphology goes digital: a research hub for cellular and system neuroscience

The importance of neuronal morphology in brain function has been recognized for over a century. The broad applicability of "digital reconstructions" of neuron morphology across neuroscience subdisciplines has stimulated the rapid development of numerous synergistic tools for data acquisition, anatomical analysis, three-dimensional rendering, electrophysiological simulation, growth models, and data sharing. Here we discuss the processes of histological labeling, microscopic imaging, and semiautomated tracing. Moreover, we provide an annotated compilation of currently available resources in this rich research "ecosystem" as a central reference for experimental and computational neuroscience.

Qualia could arise from information processing in local cortical networks

Re-entrant feedback, either within sensory cortex or arising from prefrontal areas, has been strongly linked to the emergence of consciousness, both in theoretical and experimental work. This idea, together with evidence for local micro-consciousness, suggests the generation of qualia could in some way result from local network activity under re-entrant activation. This paper explores the possibility by examining the processing of information by local cortical networks. It highlights the difference between the information structure (how the information is physically embodied), and the information message (what the information is about). It focuses on the network’s ability to recognize information structures amongst its inputs under conditions of extensive local feedback, and to then assign information messages to those structures. It is shown that if the re-entrant feedback enables the network to achieve an attractor state, then the message assigned in any given pass of information through the network is a representation of the message assigned in the previous pass-through of information. Based on this ability the paper argues that as information is repeatedly cycled through the network, the information message that is assigned evolves from a recognition of what the input structure is, to what it is like, to how it appears, to how it seems. It could enable individual networks to be the site of qualia generation. The paper goes on to show networks in cortical layers 2/3 and 5a have the connectivity required for the behavior proposed, and reviews some evidence for a link between such local cortical cyclic activity and conscious percepts. It concludes with some predictions based on the theory discussed.

Neocortical somatostatin-expressing GABAergic interneurons disinhibit the thalamorecipient layer 4

Subtypes of GABAergic interneurons (INs) are crucial for cortical function, yet their specific roles are largely unknown. In contrast to supra- and infragranular layers, where most somatostatin-expressing (SOM) INs are layer 1-targeting Martinotti cells, the axons of SOM INs in layer 4 of somatosensory cortex largely remain within layer 4. Moreover, we found that whereas layers 2/3 SOM INs target mainly pyramidal cells (PCs), layer 4 SOM INs target mainly fast-spiking (FS) INs. Accordingly, optogenetic inhibition of SOM INs in an active cortical network increases the firing of layers 2/3 PCs whereas it decreases the firing of layer 4 principal neurons (PNs). This unexpected effect of SOM INs on layer 4 PNs occurs via their inhibition of local FS INs. These results reveal a disinhibitory microcircuit in the thalamorecipient layer through interactions among subtypes of INs and suggest that the SOM IN-mediated disinhibition represents an important circuit mechanism for cortical information processing.

Computing the size and number of neuronal clusters in local circuits

The organization of connectivity in neuronal networks is fundamental to understanding the activity and function of neural networks and information processing in the brain. Recent studies show that the neocortex is not only organized in columns and layers but also, within these, into synaptically connected clusters of neurons (Ko et al., 2011; Perin et al., 2011). The recently discovered common neighbor rule, according to which the probability of any two neurons being synaptically connected grows with the number of their common neighbors, is an organizing principle for this local clustering. Here we investigated the theoretical constraints for how the spatial extent of neuronal axonal and dendritic arborization, heretofore described by morphological reach, the density of neurons and the size of the network determine cluster size and numbers within neural networks constructed according to the common neighbor rule. In the formulation we developed, morphological reach, cell density, and network size are sufficient to estimate how many neurons, on average, occur in a cluster and how many clusters exist in a given network. We find that cluster sizes do not grow indefinitely as network parameters increase, but tend to characteristic limiting values.

Revealing the secrets of neuronal circuits with recombinant rabies virus technology

An understanding of how the brain processes information requires knowledge of the architecture of its underlying neuronal circuits, as well as insights into the relationship between architecture and physiological function. A range of sophisticated tools is needed to acquire this knowledge, and recombinant rabies virus (RABV) is becoming an increasingly important part of this essential toolbox. RABV has been recognized for years for its properties as a synapse-specific trans-neuronal tracer. A novel genetically modified variant now enables the investigation of specific monosynaptic connections. This technology, in combination with other genetic, physiological, optical, and computational tools, has enormous potential for the visualization of neuronal circuits, and for monitoring and manipulating their activity. Here we will summarize the latest developments in this fast moving field and provide a perspective for the use of this technology for the dissection of neuronal circuit structure and function in the normal and diseased brain.

The organization of two new cortical interneuronal circuits

Deciphering the interneuronal circuitry is central to understanding brain functions, yet it remains a challenging task in neurobiology. Using simultaneous quadruple-octuple in vitro and dual in vivo whole-cell recordings, we found two previously unknown interneuronal circuits that link cortical layer 1-3 (L1-3) interneurons and L5 pyramidal neurons in the rat neocortex. L1 single-bouquet cells (SBCs) preferentially formed unidirectional inhibitory connections on L2/3 interneurons that inhibited the entire dendritic-somato-axonal axis of ∼1% of L5 pyramidal neurons located in the same column. In contrast, L1 elongated neurogliaform cells (ENGCs) frequently formed mutual inhibitory and electric connections with L2/3 interneurons, and these L1-3 interneurons inhibited the distal apical dendrite of >60% of L5 pyramidal neurons across multiple columns. Functionally, SBC→L2/3 interneuron→L5 pyramidal neuronal circuits disinhibited and ENGC↔L2/3 interneuron→L5 pyramidal neuronal circuits inhibited the initiation of dendritic complex spikes in L5 pyramidal neurons. As dendritic complex spikes can serve coincidence detection, these cortical interneuronal circuits may be essential for salience selection.

Efficient associative memory storage in cortical circuits of inhibitory and excitatory neurons

Many features of synaptic connectivity are ubiquitous among cortical systems. Cortical networks are dominated by excitatory neurons and synapses, are sparsely connected, and function with stereotypically distributed connection weights. We show that these basic structural and functional features of synaptic connectivity arise readily from the requirement of efficient associative memory storage. Our theory makes two fundamental predictions. First, we predict that, despite a large number of neuron classes, functional connections between potentially connected cells must be realized with <50% probability if the presynaptic cell is excitatory and >50% probability if the presynaptic cell is inhibitory. Second, we establish a unique relation between probability of connection and coefficient of variation in connection weights. These predictions are consistent with a dataset of 74 published experiments reporting connection probabilities and distributions of postsynaptic potential amplitudes in various cortical systems. What is more, our theory explains the shapes of the distributions obtained in these experiments.

The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model

In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to activity dynamics. While available comprehensive connectivity maps ( Thomson, West, et al. 2002; Binzegger et al. 2004) have been used in various computational studies, prominent features of the simulated activity such as the spontaneous firing rates do not match the experimental findings. Here, we analyze the properties of these maps to compile an integrated connectivity map, which additionally incorporates insights on the specific selection of target types. Based on this integrated map, we build a full-scale spiking network model of the local cortical microcircuit. The simulated spontaneous activity is asynchronous irregular and cell-type specific firing rates are in agreement with in vivo recordings in awake animals, including the low rate of layer 2/3 excitatory cells. The interplay of excitation and inhibition captures the flow of activity through cortical layers after transient thalamic stimulation. In conclusion, the integration of a large body of the available connectivity data enables us to expose the dynamical consequences of the cortical microcircuitry.

Subcellular synaptic connectivity of layer 2 pyramidal neurons in the medial prefrontal cortex

Pyramidal neurons in the prefrontal cortex (PFC) are important for the control of cognitive and emotional behavior. The medial PFC (mPFC) receives diverse long-range excitatory inputs from the midline thalamus, contralateral mPFC, basolateral amygdala, and ventral hippocampus. While axons from these different regions have distinct distributions in the mPFC, their functional connections at the cellular and subcellular levels remain unknown. Here, we use optogenetics to show that layer 2 pyramidal neurons in acute slices of the mouse mPFC receive excitatory inputs from each of these regions. Using a combination of optogenetics and two-photon microscopy, we then determine the subcellular properties of these inputs. We find that different types of inputs make selective contacts at the levels of both dendrites and spines. Using two-photon uncaging, we show that this subcellular targeting strongly influences synaptic efficacy in these neurons. Together, our results show that functional connectivity is finely tuned, with important implications for signal processing in the mPFC.

Synaptic energy use and supply

Neuronal computation is energetically expensive. Consequently, the brain's limited energy supply imposes constraints on its information processing capability. Most brain energy is used on synaptic transmission, making it important to understand how energy is provided to and used by synapses. We describe how information transmission through presynaptic terminals and postsynaptic spines is related to their energy consumption, assess which mechanisms normally ensure an adequate supply of ATP to these structures, consider the influence of synaptic plasticity and changing brain state on synaptic energy use, and explain how disruption of the energy supply to synapses leads to neuropathology.

Pansynaptic enlargement at adult cortical connections strengthened by experience

Behavioral experience alters the strength of neuronal connections in adult neocortex. These changes in synaptic strength are thought to be central to experience-dependent plasticity, learning, and memory. However, it is not known how changes in synaptic transmission between neurons become persistent, thereby enabling the storage of previous experience. A long-standing hypothesis is that altered synaptic strength is maintained by structural modifications to synapses. However, the extent of synaptic modifications and the changes in neurotransmission that the modifications support remain unclear. To address these questions, we recorded from pairs of synaptically connected layer 2/3 pyramidal neurons in the barrel cortex and imaged their contacts with high-resolution confocal microscopy after altering sensory experience by whisker trimming. Excitatory connections strengthened by experience exhibited larger axonal varicosities, dendritic spines, and interposed contact zones. Electron microscopy showed that contact zone size was strongly correlated with postsynaptic density area. Therefore, our findings indicate that whole synapses are larger at strengthened connections. Synaptic transmission was both stronger and more reliable following experience-dependent synapse enlargement. Hence, sensory experience modified both presynaptic and postsynaptic function. Our findings suggest that the enlargement of synaptic contacts is an integral part of long-lasting strengthening of cortical connections and, hence, of information storage in the neocortex.

Neuronal circuits underlying persistent representations despite time varying activity

BACKGROUND

Our brains are capable of remarkably stable stimulus representations despite time-varying neural activity. For instance, during delay periods in working memory tasks, while stimuli are represented in working memory, neurons in the prefrontal cortex, thought to support the memory representation, exhibit time-varying neuronal activity. Since neuronal activity encodes the stimulus, its time-varying dynamics appears to be paradoxical and incompatible with stable network stimulus representations. Indeed, this finding raises a fundamental question: can stable representations only be encoded with stable neural activity, or, its corollary, is every change in activity a sign of change in stimulus representation?

RESULTS

Here we explain how different time-varying representations offered by individual neurons can be woven together to form a coherent, time-invariant, representation. Motivated by two ubiquitous features of the neocortex-redundancy of neural representation and sparse intracortical connections-we derive a network architecture that resolves the apparent contradiction between representation stability and changing neural activity. Unexpectedly, this network architecture exhibits many structural properties that have been measured in cortical sensory areas. In particular, we can account for few-neuron motifs, synapse weight distribution, and the relations between neuronal functional properties and connection probability.

CONCLUSIONS

We show that the intuition regarding network stimulus representation, typically derived from considering single neurons, may be misleading and that time-varying activity of distributed representation in cortical circuits does not necessarily imply that the network explicitly encodes time-varying properties.

Target-specific expression of presynaptic NMDA receptors in neocortical microcircuits

Traditionally, NMDA receptors are located postsynaptically; yet, putatively presynaptic NMDA receptors (preNMDARs) have been reported. Although implicated in controlling synaptic plasticity, their function is not well understood and their expression patterns are debated. We demonstrate that, in layer 5 of developing mouse visual cortex, preNMDARs specifically control synaptic transmission at pyramidal cell inputs to other pyramidal cells and to Martinotti cells, while leaving those to basket cells unaffected. We also reveal a type of interneuron that mediates ascending inhibition. In agreement with synapse-specific expression, we find preNMDAR-mediated calcium signals in a subset of pyramidal cell terminals. A tuned network model predicts that preNMDARs specifically reroute information flow in local circuits during high-frequency firing, in particular by impacting frequency-dependent disynaptic inhibition mediated by Martinotti cells, a finding that we experimentally verify. We conclude that postsynaptic cell type determines presynaptic terminal molecular identity and that preNMDARs govern information processing in neocortical columns.

Communication and wiring in the cortical connectome

In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns.

Spike-timing dependence of structural plasticity explains cooperative synapse formation in the neocortex

Structural plasticity governs the long-term development of synaptic connections in the neocortex. While the underlying processes at the synapses are not fully understood, there is strong evidence that a process of random, independent formation and pruning of excitatory synapses can be ruled out. Instead, there must be some cooperation between the synaptic contacts connecting a single pre- and postsynaptic neuron pair. So far, the mechanism of cooperation is not known. Here we demonstrate that local correlation detection at the postsynaptic dendritic spine suffices to explain the synaptic cooperation effect, without assuming any hypothetical direct interaction pathway between the synaptic contacts. Candidate biomolecular mechanisms for dendritic correlation detection have been identified previously, as well as for structural plasticity based thereon. By analyzing and fitting of a simple model, we show that spike-timing correlation dependent structural plasticity, without additional mechanisms of cross-synapse interaction, can reproduce the experimentally observed distributions of numbers of synaptic contacts between pairs of neurons in the neocortex. Furthermore, the model yields a first explanation for the existence of both transient and persistent dendritic spines and allows to make predictions for future experiments.

Structural plasticity has been observed even in the adult mammalian neocortex – in seemingly static neuronal circuits structural remodeling is continuously at work. Still, it has been shown that the connection patterns between pairs of neurons are not random. In contrast, there is evidence that the synaptic contacts between a pair of neurons cooperate: several experimental studies report either zero or about 3–6 synapses between neuron pairs. The mechanism by which the synapses cooperate, however, has not yet been identified. Here we propose a model for structural plasticity that relies on local processes at the dendritic spine. We combine and extend the previous models and determine the equilibrium probability distribution of synaptic contact numbers of the model. By optimizing the parameters numerically for each of three reference datasets, we obtain equilibrium contact number distributions that fit the references very well. We conclude that the local dendritic mechanisms that we assume suffice to explain the cooperative synapse formation in the neocortex.

Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits

It is well-established that synapse formation involves highly selective chemospecific mechanisms, but how neuron arbors are positioned before synapse formation remains unclear. Using 3D reconstructions of 298 neocortical cells of different types (including nest basket, small basket, large basket, bitufted, pyramidal, and Martinotti cells), we constructed a structural model of a cortical microcircuit, in which cells of different types were independently and randomly placed. We compared the positions of physical appositions resulting from the incidental overlap of axonal and dendritic arbors in the model (statistical structural connectivity) with the positions of putative functional synapses (functional synaptic connectivity) in 90 synaptic connections reconstructed from cortical slice preparations. Overall, we found that statistical connectivity predicted an average of 74 ± 2.7% (mean ± SEM) synapse location distributions for nine types of cortical connections. This finding suggests that chemospecific attractive and repulsive mechanisms generally do not result in pairwise-specific connectivity. In some cases, however, the predicted distributions do not match precisely, indicating that chemospecific steering and aligning of the arbors may occur for some types of connections. This finding suggests that random alignment of axonal and dendritic arbors provides a sufficient foundation for specific functional connectivity to emerge in local neural microcircuits.

Functional impact of interneuronal inhibition in the cerebral cortex of behaving animals

This paper reviews recent progress in understanding the functional roles of inhibitory interneurons in behaving animals and how they affect information processing in cortical microcircuits. Multiple studies have shown that the morphological subtypes of inhibitory cells show distinct electrophysiological properties, as well as different molecular and neurochemical identities, providing a large mosaic of inhibitory mechanisms for the dynamic processing of information in the cortex. However, it is only recently that some specific functions of different interneuronal subtypes have been described in behaving animals. In this regard, influential results have been obtained using the known differences of interneurons and pyramidal cells recorded extracellularly to dissociate the functional roles that these two classes of neurons may play in the cortical microcircuits during various behaviors. Neurons can be segregated into fast-spiking (FS) cells that show short action potentials, high discharge rates, and correspond to putative interneurons; and regular-spiking (RS) cells that show larger action potentials and correspond to pyramidal neurons. Using this classification strategy, it has been found that cortical inhibition is involved in sculpting the tuning to different stimulus or behavioral features across a wide variety of sensory, association, and motor areas. Recent studies have suggested that the increase in high-frequency synchronization during information processing and spatial attention may be mediated by FS activation. Finally, FS are active during motor planning and movement execution in different motor areas, supporting the notion that inhibitory interneurons are involved in shaping the motor command but not in gating the cortical output.

Does spike-timing-dependent synaptic plasticity couple or decouple neurons firing in synchrony?

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5-10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity.

Neuronal communication: firing spikes with spikes

Spikes of single cortical neurons can exert powerful effects even though most cortical synapses are too weak to fire postsynaptic neurons. A recent study combining single-cell stimulation with population imaging has visualized in vivo postsynaptic firing in genetically identified target cells. The results confirm predictions from in vitro work and might help to understand how the brain reads single-neuron activity.