Michael Okun

Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities.

Temporal and quantitative relations between excitatory and inhibitory inputs in the cortex are central to its activity, yet they remain poorly understood. In particular, a controversy exists regarding the extent of correlation between cortical excitation and inhibition. Using simultaneous intracellular recordings in pairs of nearby neurons in vivo, we found that excitatory and inhibitory inputs are continuously synchronized and correlated in strength during spontaneous and sensory-evoked activities in the rat somatosensory cortex.

The Subthreshold Relation between Cortical Local Field Potential and Neuronal Firing Unveiled by Intracellular Recordings in Awake Rats

In most of the in vivo electrophysiological studies of cortical processing, which are extracellular, the spike-triggered local field potential average (LFP STA) is the measure used to estimate the correlation between the synaptic inputs of individual neuron and the local population. To understand how the magnitude and shape of LFP STA reflect the underlying correlation of synaptic activities, the membrane potential of the firing neuron has to be recorded together with the LFP. Using intracellular recordings from the cortex of awake rats, we found that for a large range of firing rates and for different behavioral states, the LFP STA represents both in its waveform and its magnitude the cross-correlation between the membrane potential of the neuron and the LFP. This data, supported by further analysis, suggests that LFP STA does not represent large network events specific to the spike times, but rather the synchrony between the mean synaptic activity of the population and the membrane potential of the single neuron, present both around spike times and in the intervals between spikes. Furthermore, it introduces a novel interpretation of the available data from unit and LFP extracellular recording experiments.

Diverse coupling of neurons to populations in sensory cortex

A large population of neurons can, in principle, produce an astronomical number of distinct firing patterns. In cortex, however, these patterns lie in a space of lower dimension, as if individual neurons were “obedient members of a huge orchestra”. Here we use recordings from the visual cortex of mouse (Mus musculus) and monkey (Macaca mulatta) to investigate the relationship between individual neurons and the population, and to establish the underlying circuit mechanisms. We show that neighbouring neurons can differ in their coupling to the overall firing of the population, ranging from strongly coupled ‘choristers’ to weakly coupled ‘soloists’. Population coupling is largely independent of sensory preferences, and it is a fixed cellular attribute, invariant to stimulus conditions. Neurons with high population coupling are more strongly affected by non-sensory behavioural variables such as motor intention. Population coupling reflects a causal relationship, predicting the response of a neuron to optogenetically driven increases in local activity. Moreover, population coupling indicates synaptic connectivity; the population coupling of a neuron, measured in vivo, predicted subsequent in vitro estimates of the number of synapses received from its neighbours. Finally, population coupling provides a compact summary of population activity; knowledge of the population couplings of n neurons predicts a substantial portion of their n2 pairwise correlations. Population coupling therefore represents a novel, simple measure that characterizes the relationship of each neuron to a larger population, explaining seemingly complex network firing patterns in terms of basic circuit variables.

The Nature of Shared Cortical Variability

Summary Neuronal responses of sensory cortex are highly variable, and this variability is correlated across neurons. To assess how variability reflects factors shared across a neuronal population, we analyzed the activity of many simultaneously recorded neurons in visual cortex. We developed a simple model that comprises two sources of shared variability: a multiplicative gain, which uniformly scales each neuron’s sensory drive, and an additive offset, which affects different neurons to different degrees. This model captured the variability of spike counts and reproduced the dependence of pairwise correlations on neuronal tuning and stimulus orientation. The relative contributions of the additive and multiplicative fluctuations could vary over time and had marked impact on population coding. These observations indicate that shared variability of neuronal populations in sensory cortex can be largely explained by two factors that modulate the whole population.

Stochastic Emergence of Repeating Cortical Motifs in Spontaneous Membrane Potential Fluctuations In Vivo

It was recently discovered that subthreshold membrane potential fluctuations of cortical neurons can precisely repeat during spontaneous activity, seconds to minutes apart, both in brain slices and in anesthetized animals. These repeats, also called cortical motifs, were suggested to reflect a replay of sequential neuronal firing patterns. We searched for motifs in spontaneous activity, recorded from the rat barrel cortex and from the cat striate cortex of anesthetized animals, and found numerous repeating patterns of high similarity and repetition rates. To test their significance, various statistics were compared between physiological data and three different types of stochastic surrogate data that preserve dynamical characteristics of the recorded data. We found no evidence for the existence of deterministically generated cortical motifs. Rather, the stochastic properties of cortical motifs suggest that they appear by chance, as a result of the constraints imposed by the coarse dynamics of subthreshold ongoing activity.

Fully integrated silicon probes for high-density recording of neural activity

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal–oxide–semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Population Rate Dynamics and Multineuron Firing Patterns in Sensory Cortex

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron “words” (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features.

Long Term Recordings with Immobile Silicon Probes in the Mouse Cortex

A key experimental approach in neuroscience involves measuring neuronal activity in behaving animals with extracellular chronic recordings. Such chronic recordings were initially made with single electrodes and tetrodes, and are now increasingly performed with high-density, high-count silicon probes. A common way to achieve long-term chronic recording is to attach the probes to microdrives that progressively advance them into the brain. Here we report, however, that such microdrives are not strictly necessary. Indeed, we obtained high-quality recordings in both head-fixed and freely moving mice for several months following the implantation of immobile chronic probes. Probes implanted into the primary visual cortex yielded well-isolated single units whose spike waveform and orientation tuning were highly reproducible over time. Although electrode drift was not completely absent, stable waveforms occurred in at least 70% of the neurons tested across consecutive days. Thus, immobile silicon probes represent a straightforward and reliable technique to obtain stable, long-term population recordings in mice, and to follow the activity of populations of well-isolated neurons over multiple days.

Agreement Among Unacquainted Byzantine Generals

The Byzantine Agreement (BA) problem introduced by Pease, Shostak and Lamport in [1] is one of the central problems in distributed computing. It was extensively studied under various timing, topology, authentication and failure assumptions. In previous works it was assumed that the network topology is known to the processors in advance, i.e., every processor has an a priori knowledge of the true unique identi.er of the processor to which it is connected by each of its communication channels (see Fig. 1a).

Balance of Excitation and Inhibition

In the context of neurophysiology, balance of excitation and inhibition (E/I balance) refers to the relative contributions of excitatory and inhibitory synaptic inputs corresponding to some neuronal event, such as oscillation or response evoked by sensory stimulation. In the current literature, owing to the extremely wide range of conditions in which the term is applied, it has several different, albeit related, meanings.