Shimon Marom

Development, learning and memory in large random networks of cortical neurons: lessons beyond anatomy

1. Introduction 63 1.1 Outline 63 1.2 Universals versus realizations in the study of learning and memory 64 2. Large random cortical networks developing ex vivo 65 2.1 Preparation 65 2.2 Measuring electrical activity 67 3. Spontaneous development 69 3.1 Activity 69 3.2 Connectivity 70 4. Consequences of spontaneous activity: pharmacological manipulations 72 4.1 Structural consequences 72 4.2 Functional consequences 73 5. Effects of stimulation 74 5.1 Response to focal stimulation 74 5.2 Stimulation-induced changes in connectivity 74 6. Embedding functionality in real neural networks 77 6.1 Facing the physiological definition of ‘reward’: two classes of theories 78 6.2 Closing the loop 79 7. Concluding remarks 84 8. Acknowledgments 85 9. References 85 The phenomena of learning and memory are inherent to neural systems that differ from each other markedly. The differences, at the molecular, cellular and anatomical levels, reflect the wealth of possible instantiations of two neural learning and memory universals: (i) an extensive functional connectivity that enables a large repertoire of possible responses to stimuli; and (ii) sensitivity of the functional connectivity to activity, allowing for selection of adaptive responses. These universals can now be fully realized in ex-vivo developing neuronal networks due to advances in multi-electrode recording techniques and desktop computing. Applied to the study of ex-vivo networks of neurons, these approaches provide a unique view into learning and memory in networks, over a wide range of spatio-temporal scales. In this review, we summarize experimental data obtained from large random developing ex-vivo cortical networks. We describe how these networks are prepared, their structure, stages of functional development, and the forms of spontaneous activity they exhibit (Sections 2–4). In Section 5 we describe studies that seek to characterize the rules of activity-dependent changes in neural ensembles and their relation to monosynaptic rules. In Section 6, we demonstrate that it is possible to embed functionality into ex-vivo networks, that is, to teach them to perform desired firing patterns in both time and space. This requires ‘closing a loop’ between the network and the environment. Section 7 emphasizes the potential of ex-vivo developing cortical networks in the study of neural learning and memory universals. This may be achieved by combining closed loop experiments and ensemble-defined rules of activity-dependent change.

Dynamics and effective topology underlying synchronization in networks of cortical neurons

Cognitive processes depend on synchronization and propagation of electrical activity within and between neuronal assemblies. In vivo measurements show that the size of individual assemblies depends on their function and varies considerably, but the timescale of assembly activation is in the range of 0.1–0.2 s and is primarily independent of assembly size. Here we use an in vitro experimental model of cortical assemblies to characterize the process underlying the timescale of synchronization, its relationship to the effective topology of connectivity within an assembly, and its impact on propagation of activity within and between assemblies. We show that the basic mode of assembly activation, “network spike,” is a threshold-governed, synchronized population event of 0.1–0.2 s duration and follows the logistics of neuronal recruitment in an effectively scale-free connected network. Accordingly, the sequence of neuronal activation within a network spike is nonrandom and hierarchical; a small subset of neurons is consistently recruited tens of milliseconds before others. Theory predicts that scale-free topology allows for synchronization time that does not increase markedly with network size; our experiments with networks of different densities support this prediction. The activity of early-to-fire neurons reliably forecasts an upcoming network spike and provides means for expedited propagation between assemblies. We demonstrate this capacity by observing the dynamics of two artificially coupled assemblies in vitro, using neuronal activity of one as a trigger for electrical stimulation of the other.

Long-term relationships between synaptic tenacity, synaptic remodeling, and network activity.

Long term time-lapse imaging reveals that individual synapses undergo significant structural remodeling not only when driven by activity, but also when network activity is absent, raising questions about how reliably individual synapses maintain connections.

STATE-DEPENDENT INACTIVATION OF THE KV3 POTASSIUM CHANNEL

Inactivation of Kv3 (Kv1.3) delayed rectifier potassium channels was studied in the Xenopus oocyte expression system. These channels inactivate slowly during a long depolarizing pulse. In addition, inactivation accumulates in response to a series of short depolarizing pulses (cumulative inactivation), although no significant inactivation occurs within each short pulse. The extent of cumulative inactivation does not depend on the voltage during the depolarizing pulse, but it does vary in a biphasic manner as a function of the interpulse duration. Furthermore, the rate of cumulative inactivation is influenced by changing the rate of deactivation. These data are consistent with a model in which Kv3 channel inactivation is a state-dependent and voltage-independent process. Macroscopic and single channel experiments indicate that inactivation can occur from a closed (silent) state before channel opening. That is, channels need not open to inactivate. The transition that leads to the inactivated state from the silent state is, in fact, severalfold faster then the observed inactivation of current during long depolarizing pulses. Long pulse-induced inactivation appears to be slow, because its rate is limited by the probability that channels are in the open state, rather than in the silent state from which they can inactivate. External potassium and external calcium ions alter the rates of cumulative and long pulse-induced inactivation, suggesting that antagonistic potassium and calcium binding steps are involved in the normal gating of the channel.

Dynamics of Excitability over Extended Timescales in Cultured Cortical Neurons

Although neuronal excitability is well understood and accurately modeled over timescales of up to hundreds of milliseconds, it is currently unclear whether extrapolating from this limited duration to longer behaviorally relevant timescales is appropriate. Here we used an extracellular recording and stimulation paradigm that extends the duration of single-neuron electrophysiological experiments, exposing the dynamics of excitability in individual cultured cortical neurons over timescales hitherto inaccessible. We show that the long-term neuronal excitability dynamics is unstable and dominated by critical fluctuations, intermittency, scale-invariant rate statistics, and long memory. These intrinsic dynamics bound the firing rate over extended timescales, contrasting observed short-term neuronal response to stimulation onset. Furthermore, the activity of a neuron over extended timescales shows transitions between quasi-stable modes, each characterized by a typical response pattern. Like in the case of rate statistics, the short-term onset response pattern that often serves to functionally define a given neuron is not indicative of its long-term ongoing response. These observations question the validity of describing neuronal excitability based on temporally restricted electrophysiological data, calling for in-depth exploration of activity over wider temporal scales. Such extended experiments will probably entail a different kind of neuronal models, accounting for the unbounded range, from milliseconds up.

Order-Based Representation in Random Networks of Cortical Neurons

The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

Neural timescales or lack thereof

This article aims at making readers, experimentalists and theorists, more aware of the abstractions made by an observer when measuring and reporting behavioral and neural timescales. These abstractions stow away the fact that, above lower boundaries that reflect fairly well understood physical constraints, observed and reported timescales are often not intrinsic to the biological system; rather, in most cases they reflect conditions that are imposed by the observer through the measuring procedure. This is true at practically every level of organization, from behavior down to molecules. I analyze the impacts of the resulting temporal manifold in behavioral and brain sciences on experimental designs and mathematical modeling.

Modeling state-dependent inactivation of membrane currents.

Inactivation of many ion channels occurs through largely voltage-independent transitions to an inactivated state from the open state or from other states in the pathway leading to opening of the channel. Because this form of inactivation is state-dependent rather than voltage-dependent, it cannot be described by the standard Hodgkin-Huxley formalism used in virtually all modeling studies of neuronal behavior. Using two examples, cumulative inactivation of the Kv3 potassium channel and inactivation of the fast sodium channel, we extend the standard formalism for modeling macroscopic membrane currents to account for state-dependent inactivation. Our results provide an accurate description of cumulative inactivation of the Kv3 channel, new insight into inactivation of the sodium channel, and a general framework for modeling macroscopic currents when state-dependent processes are involved. In a model neuron, the macroscopic Kv3 current produces a novel short-term memory effect and firing delays similar to those seen in hippocampal neurons.

Cell Therapy for Modification of the Myocardial Electrophysiological Substrate

Background— Traditional antiarrhythmic pharmacological therapies are limited by their global cardiac action, low efficacy, and significant proarrhythmic effects. We present a novel approach for the modification of the myocardial electrophysiological substrate using cell grafts genetically engineered to express specific ionic channels. Methods and Results— To test the aforementioned concept, we performed ex vivo, in vivo, and computer simulation studies to determine the ability of fibroblasts transfected to express the voltage-sensitive potassium channel Kv1.3 to modify the local myocardial excitable properties. Coculturing of the transfected fibroblasts with neonatal rat ventricular myocyte cultures resulted in a significant reduction (68%) in the spontaneous beating frequency of the cultures compared with baseline values and cocultures seeded with naive fibroblasts. In vivo grafting of the transfected fibroblasts in the rat ventricular myocardium significantly prolonged the local effective refractory period from an initial value of 84±8 ms (cycle length, 200 ms) to 154±13 ms (P<0.01). Margatoxin partially reversed this effect (effective refractory period, 117±8 ms; P<0.01). In contrast, effective refractory period did not change in nontransplanted sites (86±7 ms) and was only mildly increased in the animals injected with wild-type fibroblasts (73±5 to 88±4 ms; P<0.05). Similar effective refractory period prolongation also was found during slower pacing drives (cycle length, 350 to 500 ms) after transplantation of the potassium channels expressing fibroblasts (Kv1.3 and Kir2.1) in pigs. Computer modeling studies confirmed the in vivo results. Conclusions— Genetically engineered cell grafts, transfected to express potassium channels, can couple with host cardiomyocytes and alter the local myocardial electrophysiological properties by reducing cardiac automaticity and prolonging refractoriness.

Intracellular and extracellular amino acids that influence C-type inactivation and its modulation in a voltage-dependent potassium channel

The rate of C-type inactivation of the cloned voltage-gated potassium channel, Kv1.3, measured in membrane patches from Xenopus oocytes, increases when the patch is detached from the cell; the structural basis for this on-cell/off-cell change was examined. First, four serine and threonine residues, that are putative sites for phosphorylation by protein kinases A and C, were mutated to alanines. Mutating any one of these residues, or two or three of them simultaneously, does not eliminate the change in C-type inactivation. However, the basal rate of C-type inactivation in the cell-attached patch is markedly slower in the triple phosphorylation site mutant. Second, a homologous potassium channel, Kv 1.6, does not exhibit the on-cell/off-cell change. When an extracellular histidine at position 401 of Kv1.3 is replaced with tyrosine, the residue at the equivalent position (430) in Kv1.6, the resulting Kv1.3 H401Y mutant channel does not undergo the on-cell/off-cell change. The results indicate that several potentially phosphorylatable intracellular amino acids influence the basal rate of C-type inactivation, but are not essential for the on-cell/off-cell change in inactivation kinetics. In contrast, an extracellular amino acid is critical for this on-cell/off-cell change.