Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro

Human cell reprogramming technologies offer access to live human neurons from patients and provide a new alternative for modeling neurological disorders in vitro. Neural electrical activity is the essence of nervous system function in vivo. Therefore, we examined neuronal activity in media widely used to culture neurons. We found that classic basal media, as well as serum, impair action potential generation and synaptic communication. To overcome this problem, we designed a new neuronal medium (BrainPhys basal + serum-free supplements) in which we adjusted the concentrations of inorganic salts, neuroactive amino acids, and energetic substrates. We then tested that this medium adequately supports neuronal activity and survival of human neurons in culture. Long-term exposure to this physiological medium also improved the proportion of neurons that were synaptically active. The medium was designed to culture human neurons but also proved adequate for rodent neurons. The improvement in BrainPhys basal medium to support neurophysiological activity is an important step toward reducing the gap between brain physiological conditions in vivo and neuronal models in vitro.

Network Activity and Plasticity

Vincent Delattre

The cortex must maintain balanced levels of neural activity to correctly integrate inputs and to provide contextually meaningful outputs. Neuronal excitation is counterbalanced by various forms of inhibition such as spike frequency adaptation, short- and long-term depression at excitatory synapses, and inhibitory cell coupling. When excitatory activity is low, homeostatic mechanisms enhance network excitability. When excitation is stronger than inhibition, network bursts of activity arise that also need to be dampened lest they run out of control. A disruption of the fine balance between excitatory and inhibitory systems is observed in an increasing numbers of brain disorders such as epilepsy, mental retardation and autism. This thesis aims to study aspects of the regulation of excitation in cortical networks at a molecular, cellular, network and disease level of investigation. We present in the first chapter an investigation of the impact of network bursts on standard spike-timing dependent plasticity (STDP) events in acute cortical brain slices. We discovered that these two kinds of events, which are the most well-established ways to induce synaptic plasticity in vitro, can block each other as well as cooperate to change the amplitude and direction of plasticity. Because the outcome of the interaction depends on the precise timing of network bursts relative to a STDP event in a single synaptic pathway, the observed network-timing dependent plasticity provides a novel mechanism for the modulation of local synaptic plasticity by the network level of activity, a form of global control of local synaptic plasticity. We hypothesized that network bursts consume extracellular resources needed to potentiate, restricting potentiation to active synapses at the burst onset while yielding depression of synapses activated at later times. As we demonstrate with simulation, this simple mechanism supports paradigm-shifting implications for models of learning, solving a persistent and fundamental problem since BCM (Bienenstock Cooper Munro, 1981) to incorporate synaptic learning into realistic neuronal networks while simultaneously establishing and maintaining excitatory-inhibitory balance. The proposed mechanism also links experimental evidence for interactions between STDP and network activity to observations of self-organized criticality in neural systems, a regime known to be optimal for information coding. In the second chapter, we investigated the effect of the loss of NLGN4 protein on synapse function and on network response to electrical stimulation. The neuroligin family of genes encodes for trans-synaptic proteins involved in synaptic differentiation and maturation. Former studies have reported that both NLGN1-KO and NLGN2-KO give rise to pathologic deregulations of the balance between excitation and inhibition in neural networks, and the presence of loss-of-function mutations in NLGN4 in a small number of autistic patients indicates a possible link between Neuroligin-4 gene and autism. Using extra-cellular stimulation and intra-cellular recordings in acute brain slices, we observed a decreased response of both excitatory and inhibitory response in NLGN4-KO animals, suggesting that NLGN4 is expressed at both excitatory and inhibitory synapses. Furthermore, we observed that the NLGN4-KO resulted in a significantly larger decrease of the excitatory response than of the inhibitory response, thus yielding a hypo-excitable network. The final chapter consists of the characterization of excitatory pathways in acute slices of the somato-sensory cortex. In the first study, we used chemical stimulation to promote the emergence of spontaneous recurrent activity and observed waves of activity originating from the cortical layer five. In the second study, we performed whole-cell patch-clamping of layer five pyramidal cells along with recording local field potentials (LFP). With the systematic layer-wise application of electrical stimulation at various frequencies coupled with LFP recordings, we obtained a frequency-dependent mapping of cortical inputs at all cortical layers at both the cellular and the network levels. Using this data, we developed a virtual framework for performing an analogous mapping in the virtual cortical column of the Blue Brain Project (BBP). This helped us understand the contribution of each cell population in the network response to stimulation. The framework also served as a validation test for the BBP cortical models.

EPFL2013

Limits to high-speed simulations of spiking neural networks using general-purpose computers

Wulfram Gerstner, Friedemann Zenke

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

Frontiers Research Foundation2014

High Bandwidth Synaptic Communication and Frequency Tracking in Human Neocortex

Michele Giugliano

Neuronal firing, synaptic transmission, and its plasticity form the building blocks for processing and storage of information in the brain. It is unknown whether adult human synapses are more efficient in transferring information between neurons than rodent synapses. To test this, we recorded from connected pairs of pyramidal neurons in acute brain slices of adult human and mouse temporal cortex and probed the dynamical properties of use-dependent plasticity. We found that human synaptic connections were purely depressing and that they recovered three to four times more swiftly from depression than synapses in rodent neocortex. Thereby, during realistic spike trains, the temporal resolution of synaptic information exchange in human synapses substantially surpasses that in mice. Using information theory, we calculate that information transfer between human pyramidal neurons exceeds that of mouse pyramidal neurons by four to nine times, well into the beta and gamma frequency range. In addition, we found that human principal cells tracked fine temporal features, conveyed in received synaptic inputs, at a wider bandwidth than for rodents. Action potential firing probability was reliably phase-locked to input transients up to 1,000 cycles/s because of a steep onset of action potentials in human pyramidal neurons during spike trains, unlike in rodent neurons. Our data show that, in contrast to the widely held views of limited information transfer in rodent depressing synapses, fast recovering synapses of human neurons can actually transfer substantial amounts of information during spike trains. In addition, human pyramidal neurons are equipped to encode high synaptic information content. Thus, adult human cortical microcircuits relay information at a wider bandwidth than rodent microcircuits.