VIDEO ABSTRACT.

Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 μm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs.cell assemblies | Edelman | Hebb | brain development | learning H ebb's (1) contributions to the theory of learning and memory have shaped psychological, philosophical, and neuroscientific theories for over 60 y. Three of the concepts that he put forward were particularly important. The first defines a correlation-based learning rule, namely that when one neuron persistently drives another, then the connection between them will be strengthened. The second states that this leads to the formation of clustered synaptic coupling of neurons into cell assemblies whose network topologies are molded by experience; the third suggests that such elementary cell assemblies are synaptically linked by the same learning rule to form trains of percepts (a phase sequence), constituting thoughts (1-6). There is a vast body of evidence for all three concepts (5, 7-10).Despite this evidence, theorists have pointed out that the first postulate would cause synapses within cell assemblies to saturate, restricting their dynamic range and limiting memory storage capacity (11)(12)(13)(14)(15)(16)(17)(18)(19)(20). Experimental studies have confirmed that saturated long-term potentiation (LTP) is unfavorable to learning and memory (21,22). Although Hebb (1) had suggested a mechanism for passive weakening of unused synaptic connections, these objections suggested the need for an active depressive mechanism (16,17,23), inspiring the discoveries of long-term depression (LTD) (24) and bidirectional and spike timing-dependent plastici...

The electrochemical processes that underlie neural function manifest themselves in ceaseless spatiotemporal field fluctuations. However, extracellular fields feed back onto the electric potential across the neuronal membrane via ephaptic coupling, independent of synapses. The extent to which such ephaptic coupling alters the functioning of neurons under physiological conditions remains unclear. To address this question, we stimulated and recorded from rat cortical pyramidal neurons in slices with a 12-electrode setup. We found that extracellular fields induced ephaptically mediated changes in the somatic membrane potential that were less than 0.5 mV under subthreshold conditions. Despite their small size, these fields could strongly entrain action potentials, particularly for slow (<8 Hz) fluctuations of the extracellular field. Finally, we simultaneously measured from up to four patched neurons located proximally to each other. Our findings indicate that endogenous brain activity can causally affect neural function through field effects under physiological conditions.

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Summary Brain activity generates extracellular voltage fluctuations recorded as local field potentials (LFPs). While known that the relevant micro-variables, the ionic currents across membranes, jointly generate the macro-variables, the extracellular voltage, neither the detailed biophysical knowledge nor the required computational power has been available to model these processes. We simulated the LFP in a model of the rodent neocortical column composed of >12,000 reconstructed, multi-compartmental and spiking cortical layer 4 and 5 pyramidal neurons and basket cells, including five million dendritic and somatic compartments with voltage- and ion-dependent currents, realistic connectivity and probabilistic AMPA, NMDA and GABA synapses. We found that, depending on a number of factors, the LFP reflects local and cross-layer processing and active currents dominate the generation of LFPs rather than synaptic ones. Spike-related currents impact the LFP not only at higher frequencies but lower than 50 Hz. This work calls for re-evaluating the genesis of LFPs.

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼ 30-50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity.

The general structure of the mammalian neocortex is remarkably similar across different cortical areas. Despite certain cytoarchitectural specializations and deviations from the general blueprint, the principal organization of the neocortex is relatively uniform. It is not known, however, to what extent stereotypic synaptic pathways resemble each other between cortical areas, and how far they might reflect possible functional uniformity or specialization. Here, we show that frequency-dependent disynaptic inhibition (FDDI) is a generic circuit motif that is present in all neocortical areas we investigated (primary somatosensory, auditory and motor cortex, secondary visual cortex and medial prefrontal cortex of the developing rat). We did find, however, area-specific differences in occurrence and kinetics of FDDI and the short-term dynamics of monosynaptic connections between pyramidal cells (PCs). Connectivity between PCs, both monosynaptic and via FDDI, is higher in primary cortices. The long-term effectiveness of FDDI is likely to be limited by an activity-dependent attenuation of the PC-interneuron synaptic transmission. Our results suggest that the basic construction of neocortical synaptic pathways follows principles that are independent of modality or hierarchical order within the neocortex.

A multi-cell patch clamp study reveals the summation properties of frequency-dependent disynaptic inhibition between neocortical pyramidal cells and shows how brief bursts of activity in a few cells can synchronize the entire microcircuit.