Tim P. Vogels

Signal propagation and logic gating in networks of integrate-and-fire neurons

Transmission of signals within the brain is essential for cognitive function, but it is not clear how neural circuits support reliable and accurate signal propagation over a sufficiently large dynamic range. Two modes of propagation have been studied: synfire chains, in which synchronous activity travels through feedforward layers of a neuronal network, and the propagation of fluctuations in firing rate across these layers. In both cases, a sufficient amount of noise, which was added to previous models from an external source, had to be included to support stable propagation. Sparse, randomly connected networks of spiking model neurons can generate chaotic patterns of activity. We investigate whether this activity, which is a more realistic noise source, is sufficient to allow for signal transmission. We find that, for rate-coded signals but not for synfire chains, such networks support robust and accurate signal reproduction through up to six layers if appropriate adjustments are made in synaptic strengths. We investigate the factors affecting transmission and show that multiple signals can propagate simultaneously along different pathways. Using this feature, we show how different types of logic gates can arise within the architecture of the random network through the strengthening of specific synapses.

Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks.

Plasticity at inhibitory synapses maintains balanced excitatory and inhibitory synaptic inputs at cortical neurons. Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance could be established and maintained in an experience-dependent manner by synaptic plasticity at inhibitory synapses. We show that this mechanism provides an explanation for the sparse firing patterns observed in response to natural stimuli and fits well with a recently observed interaction of excitatory and inhibitory receptive field plasticity. The introduction of inhibitory plasticity in suitable recurrent networks provides a homeostatic mechanism that leads to asynchronous irregular network states. Further, it can accommodate synaptic memories with activity patterns that become indiscernible from the background state but can be reactivated by external stimuli. Our results suggest an essential role of inhibitory plasticity in the formation and maintenance of functional cortical circuitry.

Optimal control of transient dynamics in balanced networks supports generation of complex movements.

Populations of neurons in motor cortex engage in complex transient dynamics of large amplitude during the execution of limb movements. Traditional network models with stochastically assigned synapses cannot reproduce this behavior. Here we introduce a class of cortical architectures with strong and random excitatory recurrence that is stabilized by intricate, fine-tuned inhibition, optimized from a control theory perspective. Such networks transiently amplify specific activity states and can be used to reliably execute multidimensional movement patterns. Similar to the experimental observations, these transients must be preceded by a steady-state initialization phase from which the network relaxes back into the background state by way of complex internal dynamics. In our networks, excitation and inhibition are as tightly balanced as recently reported in experiments across several brain areas, suggesting inhibitory control of complex excitatory recurrence as a generic organizational principle in cortex.

State-Dependent Function of Neocortical Chandelier Cells

Chandelier (axoaxonic) cells (ChCs) are a distinct group of GABAergic interneurons that innervate the axon initial segments of pyramidal cells. However, their circuit role and the function of their clearly defined anatomical specificity remain unclear. Recent work has demonstrated that chandelier cells can produce depolarizing GABAergic PSPs, occasionally driving postsynaptic targets to spike. On the other hand, other work suggests that ChCs are hyperpolarizing and may have an inhibitory role. These disparate functional effects may reflect heterogeneity among ChCs. Here, using brain slices from transgenic mouse strains, we first demonstrate that, across different neocortical areas and genetic backgrounds, upper Layer 2/3 ChCs belong to a single electrophysiologically and morphologically defined population, extensively sampling Layer 1 inputs with asymmetric dendrites. Consistent with being a single cell type, we find electrical coupling between ChCs. We then investigate the effect of chandelier cell activation on pyramidal neuron spiking in several conditions, ranging from the resting membrane potential to stimuli designed to approximate in vivo membrane potential dynamics. We find that under quiescent conditions, chandelier cells are capable of both promoting and inhibiting spike generation, depending on the postsynaptic membrane potential. However, during in vivo-like membrane potential fluctuations, the dominant postsynaptic effect was a strong inhibition. Thus, neocortical chandelier cells, even from within a homogeneous population, appear to play a dual role in the circuit, helping to activate quiescent pyramidal neurons, while at the same time inhibiting active ones.

Activity-dependent dendritic spine neck changes are correlated with synaptic strength

Significance Dendritic spines are the main recipients of excitatory information in the brain, and though it is accepted that they must serve an essential function in neural circuits, their precise role remains ill-defined. Here, using minimal synaptic stimulation, we show that spine neck length correlates inversely with synaptic efficacy. In addition, we discovered a previously unidentified form of spine plasticity following a spike timing-dependent plasticity protocol, characterized by rapid shortening of spine neck length and concomitant increases in synaptic strength. These results provide new insights for our understanding of synaptic plasticity, and could provide an explanation for the presence of thousands of long-necked spines in the dendrites of pyramidal neurons, whose somatic synaptic contribution would otherwise be small or negligible. Most excitatory inputs in the mammalian brain are made on dendritic spines, rather than on dendritic shafts. Spines compartmentalize calcium, and this biochemical isolation can underlie input-specific synaptic plasticity, providing a raison d’etre for spines. However, recent results indicate that the spine can experience a membrane potential different from that in the parent dendrite, as though the spine neck electrically isolated the spine. Here we use two-photon calcium imaging of mouse neocortical pyramidal neurons to analyze the correlation between the morphologies of spines activated under minimal synaptic stimulation and the excitatory postsynaptic potentials they generate. We find that excitatory postsynaptic potential amplitudes are inversely correlated with spine neck lengths. Furthermore, a spike timing-dependent plasticity protocol, in which two-photon glutamate uncaging over a spine is paired with postsynaptic spikes, produces rapid shrinkage of the spine neck and concomitant increases in the amplitude of the evoked spine potentials. Using numerical simulations, we explore the parameter regimes for the spine neck resistance and synaptic conductance changes necessary to explain our observations. Our data, directly correlating synaptic and morphological plasticity, imply that long-necked spines have small or negligible somatic voltage contributions, but that, upon synaptic stimulation paired with postsynaptic activity, they can shorten their necks and increase synaptic efficacy, thus changing the input/output gain of pyramidal neurons.

Inhibitory synaptic plasticity: spike timing-dependence and putative network function

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical findings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Unmasking Latent Inhibitory Connections in Human Cortex to Reveal Dormant Cortical Memories

Summary Balance of cortical excitation and inhibition (EI) is thought to be disrupted in several neuropsychiatric conditions, yet it is not clear how it is maintained in the healthy human brain. When EI balance is disturbed during learning and memory in animal models, it can be restabilized via formation of inhibitory replicas of newly formed excitatory connections. Here we assess evidence for such selective inhibitory rebalancing in humans. Using fMRI repetition suppression we measure newly formed cortical associations in the human brain. We show that expression of these associations reduces over time despite persistence in behavior, consistent with inhibitory rebalancing. To test this, we modulated excitation/inhibition balance with transcranial direct current stimulation (tDCS). Using ultra-high-field (7T) MRI and spectroscopy, we show that reducing GABA allows cortical associations to be re-expressed. This suggests that in humans associative memories are stored in balanced excitatory-inhibitory ensembles that lie dormant unless latent inhibitory connections are unmasked. Video Abstract

Non-normal amplification in random balanced neuronal networks

In dynamical models of cortical networks, the recurrent connectivity can amplify the input given to the network in two distinct ways. One is induced by the presence of near-critical eigenvalues in the connectivity matrix W, producing large but slow activity fluctuations along the corresponding eigenvectors (dynamical slowing). The other relies on W not being normal, which allows the network activity to make large but fast excursions along specific directions. Here we investigate the trade-off between non-normal amplification and dynamical slowing in the spontaneous activity of large random neuronal networks composed of excitatory and inhibitory neurons. We use a Schur decomposition of W to separate the two amplification mechanisms. Assuming linear stochastic dynamics, we derive an exact expression for the expected amount of purely non-normal amplification. We find that amplification is very limited if dynamical slowing must be kept weak. We conclude that, to achieve strong transient amplification with little slowing, the connectivity must be structured. We show that unidirectional connections between neurons of the same type together with reciprocal connections between neurons of different types, allow for amplification already in the fast dynamical regime. Finally, our results also shed light on the differences between balanced networks in which inhibition exactly cancels excitation and those where inhibition dominates.

Gating deficits in model networks: a path to schizophrenia?

Gating deficits and hallucinatory sensations are prominent symptoms of schizophrenia. Comparing these abnormalities with the failure modes of network models is an interesting way to explore how they arise. We present a network model that can both propagate and gate signals. The model exhibits effects reminiscent of clinically observed pathologies when the balance between excitation and inhibition that it requires is not properly maintained.

Inhibitory engrams in perception and memory.

Nervous systems use excitatory cell assemblies to encode and represent sensory percepts. Similarly, synaptically connected cell assemblies or “engrams” are thought to represent memories of past experience. Multiple lines of recent evidence indicate that brain systems create and use inhibitory replicas of excitatory representations for important cognitive functions. Such matched “inhibitory engrams” can form through homeostatic potentiation of inhibition onto postsynaptic cells that show increased levels of excitation. Inhibitory engrams can reduce behavioral responses to familiar stimuli, thereby resulting in behavioral habituation. In addition, by preventing inappropriate activation of excitatory memory engrams, inhibitory engrams can make memories quiescent, stored in a latent form that is available for context-relevant activation. In neural networks with balanced excitatory and inhibitory engrams, the release of innate responses and recall of associative memories can occur through focused disinhibition. Understanding mechanisms that regulate the formation and expression of inhibitory engrams in vivo may help not only to explain key features of cognition but also to provide insight into transdiagnostic traits associated with psychiatric conditions such as autism, schizophrenia, and posttraumatic stress disorder.