Correlated Network Activity Research Articles

From ensembles to meta-ensembles: Specific reward encoding by correlated network activity.

Neuronal ensembles are local, sparsely distributed populations of neurons that are reliably re-activated by a specific stimulus, context or task. Such discrete cell populations can be defined either functionally, by electrophysiological recordings or in vivo calcium imaging, or anatomically, using the expression of markers such as the immediate early gene cFos. A typical example of tasks that involve the formation of neuronal ensembles is reward learning, such as the cue-reward pairing during operant conditioning. These ensembles are re-activated during cue-presentation and increasing evidence suggests that this re-activation is the neurophysiological basis for the execution of reward-seeking behavior. Whilst the pursuit of rewards is a common daily activity, it is also related to the consumption of drugs, such as alcohol, and may result in problematic behaviors including addiction. Recent research has identified neuronal ensembles in several reward-related brain regions that control distinct aspects of a conditioned response, e.g., contextual information about the availability of a specific reward or the actions needed to retrieve this reward under the given circumstances. Here, we review studies using the activity marker cFos to identify and characterize neuronal ensembles related to alcohol and non-drug rewards with a special emphasis on the discrimination between different rewards by meta-ensembles, i.e., by dynamic co-activation of multiple ensembles across different brain areas.

Spontaneous Cell Cluster Formation in Human iPSC-Derived Neuronal Spheroid Networks Influences Network Activity.

Three-dimensional neuronal culture systems such as spheroids, organoids, and assembloids constitute a branch of neuronal tissue engineering that has improved our ability to model the human brain in the laboratory. However, the more elaborate the brain model, the more difficult it becomes to study functional properties such as electrical activity at the neuronal level, similar to the challenges of studying neurophysiology in vivo We describe a simple approach to generate self-assembled three-dimensional neuronal spheroid networks with defined human cell composition on microelectrode arrays. Such spheroid networks develop a highly three-dimensional morphology with cell clusters up to 60 µm in thickness and are interconnected by pronounced bundles of neuronal fibers and glial processes. We could reliably record from up to hundreds of neurons simultaneously per culture for ≤90 d. By quantifying the formation of these three-dimensional structures over time, while regularly monitoring electrical activity, we were able to establish a strong link between spheroid morphology and network activity. In particular, the formation of cell clusters accelerates formation and maturation of correlated network activity. Astrocytes both influence electrophysiological network activity as well as accelerate the transition from single cell layers to cluster formation. Higher concentrations of astrocytes also have a strong effect of modulating synchronized network activity. This approach thus represents a practical alternative to often complex and heterogeneous organoids, providing easy access to activity within a brain-like 3D environment.Significance StatementNeuronal "organoid" cultures with multiple cell types grown on elaborate three-dimensional scaffolds have become popular tools to generate brain-like properties in vitro but bring with them similar problems concerning access to physiological function as real brain tissue. Here, we developed a new approach to form simple brain-like spheroid networks from human neurons, but using the normal supporting cells of the brain, astrocytes, as the scaffold. By growing these cultures on conventional microelectrode arrays, we were able to observe development of complex patterns of electrical activity for months. Our results highlight how formation of three-dimensional structures accelerated the formation of synchronized neuronal network activity and provide a promising new simple model system for studying interactions between known human cell types in vitro.

Development of visual response selectivity in cortical GABAergic interneurons

The visual cortex of carnivores and primates displays a high degree of modular network organization characterized by local clustering and structured long-range correlations of activity and functional properties. Excitatory networks display modular organization before the onset of sensory experience, but the developmental timeline for modular networks of GABAergic interneurons remains under-explored. Using in vivo calcium imaging of the ferret visual cortex, we find evidence that before visual experience, interneurons display weak orientation tuning and widespread, correlated activity in response to visual stimuli. Robust modular organization and orientation tuning are evident with as little as one week of visual experience. Furthermore, we find that the maturation of orientation tuning requires visual experience, while the reduction in widespread, correlated network activity does not. Thus, the maturation of inhibitory cortical networks occurs in a delayed, parallel process relative to excitatory neurons.

Resting state connectivity in neocortical epilepsy: The epilepsy network as a patient-specific biomarker

ObjectiveLocalization related epilepsy (LRE) is increasingly accepted as a network disorder. To better understand the network specific characteristics of LRE, we defined individual epilepsy networks and compared them across patients. MethodsThe epilepsy network was defined in the slow cortical potential frequency band in 10 patients using intracranial EEG data obtained during interictal periods. Cortical regions were included in the epilepsy network if their connectivity pattern was similar to the connectivity pattern of the seizure onset electrode contact. Patients were subdivided into frontal, temporal, and posterior quadrant cohorts according to the anatomic location of seizure onset. Jaccard similarity was calculated within each cohort to assess for similarity of the epilepsy network between patients within each cohort. ResultsAll patients exhibited an epilepsy network in the slow cortical potential frequency band. The topographic distribution of this correlated network activity was found to be unique at the single subject level. ConclusionsThe epilepsy network was unique at the single patient level, even between patients with similar seizure onset locations. SignificanceWe demonstrated that the epilepsy network is patient-specific. This is in keeping with our current understanding of brain networks and identifies the patient-specific epilepsy network as a possible biomarker in LRE.

Early Correlated Network Activity in the Hippocampus: Its Putative Role in Shaping Neuronal Circuits

Synchronized neuronal activity occurring at different developmental stages in various brain structures represents a hallmark of developmental circuits. This activity, which differs in its specific patterns among animal species may play a crucial role in de novo formation and in shaping neuronal networks. In the rodent hippocampus in vitro, the so-called giant depolarizing potentials (GDPs) constitute a primordial form of neuronal synchrony preceding more organized forms of activity such as oscillations in the theta and gamma frequency range. GDPs are generated at the network level by the interaction of the neurotransmitters glutamate and GABA which, immediately after birth, exert both a depolarizing and excitatory action on their targets. GDPs are triggered by GABAergic interneurons, which in virtue of their extensive axonal branching operate as functional hubs to synchronize large ensembles of cells. Intrinsic bursting activity, driven by a persistent sodium conductance and facilitated by the low expression of Kv7.2 and Kv7.3 channel subunits, responsible for IM, exerts a permissive role in GDP generation. Here, we discuss how GDPs are generated in a probabilistic way when neuronal excitability within a local circuit reaches a certain threshold and how GDP-associated calcium transients act as coincident detectors for enhancing synaptic strength at emerging GABAergic and glutamatergic synapses. We discuss the possible in vivo correlate of this activity. Finally, we debate recent data showing how, in several animal models of neuropsychiatric disorders including autism, a GDPs dysfunction is associated to morphological alterations of neuronal circuits and behavioral deficits reminiscent of those observed in patients.

Functional Calcium Imaging in Developing Cortical Networks

A hallmark pattern of activity in developing nervous systems is spontaneous, synchronized network activity. Synchronized activity has been observed in intact spinal cord, brainstem, retina, cortex and dissociated neuronal culture preparations. During periods of spontaneous activity, neurons depolarize to fire single or bursts of action potentials, activating many ion channels. Depolarization activates voltage-gated calcium channels on dendrites and spines that mediate calcium influx. Highly synchronized electrical activity has been measured from local neuronal networks using field electrodes. This technique enables high temporal sampling rates but lower spatial resolution due to integrated read-out of multiple neurons at one electrode. Single cell resolution of neuronal activity is possible using patch-clamp electrophysiology on single neurons to measure firing activity. However, the ability to measure from a network is limited to the number of neurons patched simultaneously, and typically is only one or two neurons. The use of calcium-dependent fluorescent indicator dyes has enabled the measurement of synchronized activity across a network of cells. This technique gives both high spatial resolution and sufficient temporal sampling to record spontaneous activity of the developing network. A key feature of newly-forming cortical and hippocampal networks during pre- and early postnatal development is spontaneous, synchronized neuronal activity (Katz & Shatz, 1996; Khaziphov & Luhmann, 2006). This correlated network activity is believed to be essential for the generation of functional circuits in the developing nervous system (Spitzer, 2006). In both primate and rodent brain, early electrical and calcium network waves are observed pre- and postnatally in vivo and in vitro (Adelsberger et al., 2005; Garaschuk et al., 2000; Lamblin et al., 1999). These early activity patterns, which are known to control several developmental processes including neuronal differentiation, synaptogenesis and plasticity (Rakic & Komuro, 1995; Spitzer et al., 2004) are of critical importance for the correct development and maturation of the cortical circuitry. In this JoVE video, we demonstrate the methods used to image spontaneous activity in developing cortical networks. Calcium-sensitive indicators, such as Fura 2-AM ester diffuse across the cell membrane where intracellular esterase activity cleaves the AM esters to leave the cell-impermeant form of indicator dye. The impermeant form of indicator has carboxylic acid groups which are able to then detect and bind calcium ions intracellularly.. The fluorescence of the calcium-sensitive dye is transiently altered upon binding to calcium. Single or multi-photon imaging techniques are used to measure the change in photons being emitted from the dye, and thus indicate an alteration in intracellular calcium. Furthermore, these calcium-dependent indicators can be combined with other fluorescent markers to investigate cell types within the active network.

Functional Calcium Imaging in Developing Cortical Networks

A hallmark pattern of activity in developing nervous systems is spontaneous, synchronized network activity. Synchronized activity has been observed in intact spinal cord, brainstem, retina, cortex and dissociated neuronal culture preparations. During periods of spontaneous activity, neurons depolarize to fire single or bursts of action potentials, activating many ion channels. Depolarization activates voltage-gated calcium channels on dendrites and spines that mediate calcium influx. Highly synchronized electrical activity has been measured from local neuronal networks using field electrodes. This technique enables high temporal sampling rates but lower spatial resolution due to integrated read-out of multiple neurons at one electrode. Single cell resolution of neuronal activity is possible using patch-clamp electrophysiology on single neurons to measure firing activity. However, the ability to measure from a network is limited to the number of neurons patched simultaneously, and typically is only one or two neurons. The use of calcium-dependent fluorescent indicator dyes has enabled the measurement of synchronized activity across a network of cells. This technique gives both high spatial resolution and sufficient temporal sampling to record spontaneous activity of the developing network.A key feature of newly-forming cortical and hippocampal networks during pre- and early postnatal development is spontaneous, synchronized neuronal activity (Katz & Shatz, 1996; Khaziphov & Luhmann, 2006). This correlated network activity is believed to be essential for the generation of functional circuits in the developing nervous system (Spitzer, 2006). In both primate and rodent brain, early electrical and calcium network waves are observed pre- and postnatally in vivo and in vitro (Adelsberger et al., 2005; Garaschuk et al., 2000; Lamblin et al., 1999). These early activity patterns, which are known to control several developmental processes including neuronal differentiation, synaptogenesis and plasticity (Rakic & Komuro, 1995; Spitzer et al., 2004) are of critical importance for the correct development and maturation of the cortical circuitry.In this JoVE video, we demonstrate the methods used to image spontaneous activity in developing cortical networks. Calcium-sensitive indicators, such as Fura 2-AM ester diffuse across the cell membrane where intracellular esterase activity cleaves the AM esters to leave the cell-impermeant form of indicator dye. The impermeant form of indicator has carboxylic acid groups which are able to then detect and bind calcium ions intracellularly.. The fluorescence of the calcium-sensitive dye is transiently altered upon binding to calcium. Single or multi-photon imaging techniques are used to measure the change in photons being emitted from the dye, and thus indicate an alteration in intracellular calcium. Furthermore, these calcium-dependent indicators can be combined with other fluorescent markers to investigate cell types within the active network.

Scaling of a biophysical neocortical attractor model using Parallel NEURON on the Blue Gene /P

This work entails scaling a biophysical model of the neocortex using parallel NEURON [1] while running on a Blue Gene / P in virtual node mode. Previous scaling experiments have been done with the SPLIT simulator on the Blue Gene / L with a similar neocortical model [2]. We chose a biophysical model of medium complexity based on the Hodgkin-Huxley formalism because this provides the capability of exploring the effects of psychotropic drugs as well as the oscillatory effects of cortical microcircuits and globally correlated network activity. Neocortical simulations were performed to determine both strong (fixed network size, increasing cores) and weak (increasing network size, fixed load per core) scaling with two variations of a square necortical patch of hypercolumns and internal minicolumns. The first variation consists of minicolumns with 20 layer 2/3 pyramidal cells, 2 basket cells and 5 layer 4 pyramidal cells and has orthogonally stored memory patterns, encoded with long-range excitatory connections between individual minicolumns across hypercolumns. The second variation has an additional 2 regular spiking non-pyramidal interneurons per minicolumn and instead uses sparse, randomly overlapping memory patterns encoded with both excitatory and inhibitory long-range connections between hypercolumns. Simulations were performed with both single patches of increasing area and cascades of multiple patches with feed-forward and feed-backward projections. Individual simulations consisted of stimulation and completion of a single memory pattern within 1 second of cortical activity. Preliminary results show near linear speedups of the computational part of the simulation, but degradation of file I/O performance as the number of cores increase. Since each core writes out spiking activity after the simulation, the performance decline may be due to the ratio of core to I/O nodes and the large number of output files. With this performance analysis, further work will include measuring and scaling memory storage capacity with the described second variation of the biophysical neocortical model. Figure 1 Strong and weak scaling results from simulations of the first variation of the neocortical model. The blue lines represent combined initialization and simulation time and the black lines also include writing spiking output. A. Strong scaling of a 16x16 ...

The immature brain needs GABA to be excited and hyper-excited

The immature brain needs GABA to be excited and hyper-excited

Changes in brain network activity during working memory tasks: A magnetoencephalography study

In this study, we elucidate the changes in neural oscillatory processes that are induced by simple working memory tasks. A group of eight subjects took part in modified versions of the N-back and Sternberg working memory paradigms. Magnetoencephalography (MEG) data were recorded, and subsequently processed using beamformer based source imaging methodology. Our study shows statistically significant increases in θ oscillations during both N-back and Sternberg tasks. These oscillations were shown to originate in the medial frontal cortex, and further to scale with memory load. We have also shown that increases in θ oscillations are accompanied by decreases in β and γ band oscillations at the same spatial coordinate. These decreases were most prominent in the 20–40Hz frequency range, although spectral analysis showed that γ band power decrease extends up to at least 80Hz. β/γ Power decrease also scales with memory load. Whilst θ increases were predominately observed in the medial frontal cortex, β/γ decreases were associated with other brain areas, including nodes of the default mode network (for the N-back task) and areas associated with language processing (for the Sternberg task). These observations are in agreement with intracranial EEG and fMRI studies. Finally, we have shown an intimate relationship between changes in β/γ band oscillatory power at spatially separate network nodes, implying that activity in these nodes is not reflective of uni-modal task driven changes in spatially separate brain regions, but rather represents correlated network activity. The utility of MEG as a non-invasive means to measure neural oscillatory modulation has been demonstrated and future studies employing this technology have the potential to gain a better understanding of neural oscillatory processes, their relationship to functional and effective connectivity, and their correspondence to BOLD fMRI.

Traveling waves in developing cerebellar cortex mediated by asymmetrical Purkinje cell connectivity

Correlated network activity is important in the development of many neural circuits. Purkinje cells are among the first neurons to populate the cerebellar cortex, where they sprout exuberant axon collaterals. We used multiple patch-clamp recordings targeted with two-photon microscopy to characterize monosynaptic connections between the Purkinje cells of juvenile mice. We found that Purkinje cell axon collaterals projected asymmetrically in the sagittal plane, directed away from the lobule apex. On the basis of our anatomical and physiological characterization of this connection, we constructed a network model that robustly generated waves of activity that traveled along chains of connected Purkinje cells. Consistent with the model, we observed traveling waves of activity in Purkinje cells in sagittal slices from young mice that require GABA(A) receptor-mediated transmission and intact Purkinje cell axon collaterals. These traveling waves are absent in adult mice, suggesting they have a developmental role in wiring the cerebellar cortical microcircuit.

Traveling waves in developing cerebellar cortex mediated by asymmetrical Purkinje cell connectivity

Correlated network activity plays a critical role in the development of many neural circuits. Purkinje cells are among the first neurons to populate the cerebellar cortex, where they sprout exuberant axon collaterals. Here we use multiple patch-clamp recordings targeted with two-photon microscopy to characterize monosynaptic connections between Purkinje cells of juvenile mice. We show that Purkinje cell axon collaterals project asymmetrically in the sagittal plane, directed away from the lobule apex. Based on our anatomical and physiological characterization of this connection, we construct a network model that robustly generates waves of activity traveling along chains of connected Purkinje cells. Consistent with the model, we observe traveling waves of activity in Purkinje cells in sagittal slices from young mice that require GABAA receptor-mediated transmission and intact Purkinje cell axon collaterals. These traveling waves are absent in adult animals, suggesting they play a developmental role in wiring the cerebellar cortical microcircuit.

Localization of correlated network activity at the cortical level with MEG

In both hemodynamic and neurophysiological imaging methods, analysis of functionally interconnected networks has typically focused on brain areas that show strong activation in specific tasks. Alternatively, connectivity measures may be used directly to localize network nodes, independent of their level of activation. This approach requires initial cortical reference areas which may be identified based on their high level of activation, their coherence with an external reference signal, or their strong connectivity with other brain areas. Irrespective of how the nodes have been localized the mathematical complexity of the analysis methods precludes verification of the accuracy and completeness of the network structure by direct comparison with the measured data. Therefore, it is critical to understand how the choices of parameters and procedures used in the analysis affect the network identification. Here, using simulated and measured magnetoencephalography (MEG) data, and Dynamic Imaging of Coherent Sources (DICS) for connectivity analysis, we quantify the veracity of network detection at the individual and group level as a function of relevant parameter choices. Using simulations, we demonstrate that coupling measures enable accurate identification of the network structure even without external reference signals, and illustrate the applicability of this approach to real data. We show that a valid estimate of interindividual variability is critical for reliable group-level analysis. Although this study focuses on application of DICS to MEG data, many issues considered here, especially those regarding individual vs. group-level analysis, are likely to be relevant for other neuroimaging methods and analysis approaches as well.

Correlated network activity enhances synaptic efficacy via BDNF and the ERK pathway at immature CA3–CA1 connections in the hippocampus

At early developmental stages, correlated neuronal activity is thought to exert a critical control on functional and structural refinement of synaptic connections. In the hippocampus, between postnatal day 2 (P2) and P6, network-driven giant depolarizing potentials (GDPs) are generated by the synergistic action of glutamate and GABA, which is depolarizing and excitatory. Here the rising phase of GDPs was used to trigger Schaffer collateral stimulation in such a way that synchronized network activity was coincident with presynaptic activation of afferent input. This procedure produced a persistent increase in spontaneous and evoked alpha-amino-3-hydroxy-5-methyl-4-isoxadepropionic acid-mediated glutamatergic currents, an effect that required calcium influx through postsynaptic L-type calcium channels. No potentiation was observed when a delay of 3 sec was introduced between GDPs and afferent stimulation. Pairing-induced potentiation was prevented by scavengers of endogenous BDNF or tropomyosin-related kinase receptor B (TrkB) receptor antagonists. Blocking TrkB receptors in the postsynaptic cell did not prevent the effects of pairing, suggesting that BDNF, possibly secreted from the postsynaptic cell during GDPs, acts on TrkB receptors localized on presynaptic neurons. Application of exogenous BDNF mimicked the effects of pairing on synaptic transmission. In addition, pairing-induced synaptic potentiation was blocked by ERK inhibitors, suggesting that BDNF activates the MAPK/ERK cascade, which may lead to transcriptional regulation and new protein synthesis in the postsynaptic neuron. These results support the hypothesis that, during a critical period of postnatal development, GABAA-mediated GDPs are instrumental in tuning excitatory synaptic connections and provide insights into the molecular mechanisms involved in this process.

Brain activation and hypothalamic functional connectivity during human non-rapid eye movement sleep: an EEG/fMRI study

Regional differences in sleep EEG dynamics indicate that sleep-related brain activity involves local brain processes with sleep stage specific activity patterns of neuronal populations. Macroscopically, it is not fully understood which cerebral brain regions are involved in the successive discontinuation of wakefulness. We simultaneously used EEG and functional MRI on 9 subjects (6 female: mean = 24.1 years, 3 male: mean = 26.0 years) and analyzed local blood oxygenation level dependent signal changes linked to the transition from wakefulness to different non-rapid eye movement (NREM) sleep stages (according to Rechtschaffen and Kales) of the first sleep cycles after 36 h of total sleep deprivation. Several brain regions throughout the cortex, the limbic lobe, the thalamus, the caudate nucleus, as well as midbrain structures, such as the mammillary body/hypothalamus, showed reduced activity during NREM sleep across all sleep stages. Additionally, we found deactivation patterns specific to NREM sleep stages compared with wakefulness suggesting that a synchronized sleeping state can be established only if these regions interact in a well-balanced way. Sleep stage 2, which is usually linked to the loss of self-conscious awareness, is associated with signal decreases comprising thalamic and hypothalamic regions, the cingulate cortex, the right insula and adjacent regions of the temporal lobe, the inferior parietal lobule and the inferior/middle frontal gyri. The hypothalamic region known to be of particular importance in the regulation of the sleep-wake cycle shows specific temporally correlated network activity with the cortex while the system is in the sleeping state, but not during wakefulness. We describe a specific pattern of decreased brain activity during sleep and suggest that this pattern must be synchronized for establishing and maintaining sleep.

Supervised Learning Through Neuronal Response Modulation

Neural networks that are trained to perform specific tasks must be developed through a supervised learning procedure. This normally takes the form of direct supervision of synaptic plasticity. We explore the idea that supervision takes place instead through the modulation of neuronal excitability. Such supervision can be done using conventional synaptic feedback pathways rather than requiring the hypothetical actions of unknown modulatory agents. During task learning, supervised response modulation guides Hebbian synaptic plasticity indirectly by establishing appropriate patterns of correlated network activity. This results in robust learning of function approximation tasks evenwhenmultiple output units representing different functions share large amounts of common input. Reward-based supervision is also studied, and a number of potential advantages of neuronal response modulation are identified.

Spontaneous network activity of cerebellar granule neurons: impairment by in vivo chronic cannabinoid administration.

Synchronized activity of neuronal networks has been proposed to be essential for cerebellar function. To examine the occurrence and organization of spontaneous neuronal activity in the cerebellum in vivo, we imaged mouse cerebellar slices loaded with the intracellular Ca2+ concentration indicator, fura-2. Recordings were then analysed statistically to identify correlated network activity. Ca2+ imaging revealed consistent spontaneous correlated network activity of granule cells (GC), which often occurred in clusters of coactivated GC. The number of spontaneously active GC, their activation frequency and correlation, were controlled by glutamate and GABA ionotropic receptors. These findings indicate that distinctive patterns of correlated activity between GC networks may be relevant for cerebellar circuit function. Cannabinoid antagonist-precipitated delta9-tetrahydrocannabinol (THC) withdrawal impaired motor coordination. Given that the cerebellum has been suggested recently to be a main substrate for cannabinoid withdrawal, we used imaging of spontaneous network activity to examine whether GC, which contain CB1 cannabinoid receptors, respond to chronic THC treatment and withdrawal. Acute administration of THC had no effect on patterns of spontaneous GC network activity. In contrast, chronic THC administration severely impaired GC activity and network coordination. Incubation of cerebellar slices, from chronically THC-treated mice, with the cannabinoid antagonist, SR141716A increased the number and network correlation of active GC. These data provide physiological evidence of the involvement of cerebellar circuits in the adaptive changes occurring during chronic THC exposure and withdrawal.

Complex interactions between mGluR1 and mGluR5 shape neuronal network activity in the rat hippocampus

Group I metabotropic glutamate receptors (mGluRs) cause increased neuronal excitability that can lead to epileptogenesis and neurodegeneration. Here we have examined how individual members of this subgroup of mGluRs affect synchronised hippocampal synaptic activity under normal and disinhibited conditions similar to those that occur during certain epileptic states. We demonstrate that activation of both mGluR1 and mGluR5 are important in increasing neuronal synaptic excitability by increasing synchrony between cells and driving correlated network activity in circuits that contain, or are devoid of, GABA A receptor-mediated synaptic inputs. The precise patterning of activity that occurs is complex and depends upon: (1) the existing pattern of ongoing network activity prior to mGluR activation; and (2) the relative extent of activation of each mGluR subtype. However, mGluR5 appears to be the principal mGluR subtype that initiates bursting activity irrespective of the inhibitory synaptic tone within the neuronal network.

Activity-dependent development of axonal and dendritic delays, or, why synaptic transmission should be unreliable.

Systematic temporal relations between single neuronal activities or population activities are ubiquitous in the brain. No experimental evidence, however, exists for a direct modification of neuronal delays during Hebbian-type stimulation protocols. We show that in fact an explicit delay adaptation is not needed if one assumes that the synaptic strengths are modified according to the recently observed temporally asymmetric learning rule with the downregulating branch dominating the upregulating branch. During development, slow, unbiased fluctuations in the transmission time, together with temporally correlated network activity, may control neural growth and implicitly induce drifts in the axonal delays and dendritic latencies. These delays and latencies become optimally tuned in the sense that the synaptic response tends to peak in the soma of the postsynaptic cell if this is most likely to fire. The nature of the selection process requires unreliable synapses in order to give successful synapses an evolutionary advantage over the others. The width of the learning function also determines the preferred dendritic delay and the preferred width of the postsynaptic response. Hence, it may implicitly determine whether a synaptic connection provides a precisely timed or a broadly tuned "contextual" signal.