Fred Wolf

Unique features of action potential initiation in cortical neurons

Neurons process and encode information by generating sequences of action potentials. For all spiking neurons, the encoding of single-neuron computations into sequences of spikes is biophysically determined by the cells action-potential-generating mechanism. It has recently been discovered that apparently minor modifications of this mechanism can qualitatively change the nature of neuronal encoding. Here we quantitatively analyse the dynamics of action potential initiation in cortical neurons in vivo, in vitro and in computational models. Unexpectedly, key features of the initiation dynamics of cortical neuron action potentials—their rapid initiation and variable onset potential—are outside the range of behaviours described by the classical Hodgkin–Huxley theory. We propose a new model based on the cooperative activation of sodium channels that reproduces the observed dynamics of action potential initiation. This new model predicts that Hodgkin–Huxley-type dynamics of action potential initiation can be induced by artificially decreasing the effective density of sodium channels. In vitro experiments confirm this prediction, supporting the hypothesis that cooperative sodium channel activation underlies the dynamics of action potential initiation in cortical neurons.

Erythropoietin enhances hippocampal long-term potentiation and memory

BackgroundErythropoietin (EPO) improves cognition of human subjects in the clinical setting by as yet unknown mechanisms. We developed a mouse model of robust cognitive improvement by EPO to obtain the first clues of how EPO influences cognition, and how it may act on hippocampal neurons to modulate plasticity.ResultsWe show here that a 3-week treatment of young mice with EPO enhances long-term potentiation (LTP), a cellular correlate of learning processes in the CA1 region of the hippocampus. This treatment concomitantly alters short-term synaptic plasticity and synaptic transmission, shifting the balance of excitatory and inhibitory activity. These effects are accompanied by an improvement of hippocampus dependent memory, persisting for 3 weeks after termination of EPO injections, and are independent of changes in hematocrit. Networks of EPO-treated primary hippocampal neurons develop lower overall spiking activity but enhanced bursting in discrete neuronal assemblies. At the level of developing single neurons, EPO treatment reduces the typical increase in excitatory synaptic transmission without changing the number of synaptic boutons, consistent with prolonged functional silencing of synapses.ConclusionWe conclude that EPO improves hippocampus dependent memory by modulating plasticity, synaptic connectivity and activity of memory-related neuronal networks. These mechanisms of action of EPO have to be further exploited for treating neuropsychiatric diseases.

Spontaneous pinwheel annihilation during visual development

Neurons in the visual cortex respond preferentially to edge-like stimuli of a particular orientation. It is a long-standing hypothesis that orientation selectivity arises during development through the activity-dependent refinement of cortical circuitry. Unambiguous evidence for such a process has, however, remained elusive. Here we argue that, if orientation preferences arise through activity-dependent refinement of initially unselective patterns of synaptic connections, this process should leave distinct signatures in the emerging spatial pattern of preferred orientations. Preferred orientations typically change smoothly and progressively across the cortex. This smooth progression is disrupted at the centres of so-called pinwheels,, where neurons exhibiting the whole range of orientation preferences are located in close vicinity. Assuming that orientation selectivity develops through a set of rules that we do not specify, we demonstrate mathematically that the spatial density of pinwheels is rigidly constrained by basic symmetry principles. In particular, the spatial density of pinwheels, which emerge when orientation selectivity is first established, is larger than a model-independent minimal value. As a consequence, lower densities, if observed in adult animals, are predicted to develop through the motion and annihilation of pinwheel pairs.

Universality in the Evolution of Orientation Columns in the Visual Cortex

Orientation Columns In the brains visual cortex, certain neurons respond to vertical lines and others to horizontal lines, with a range in between. Such orientation of neurons tends to be organized in columns reflecting similar responses, and the columns are organized in pinwheels representing the range of responses. Kaschube et al. (p. 1113, published online 4 November; see the Perspective by Miller) looked at the organization of orientation columns in diverse placental mammals and discovered a similarity of organizational principles. Analysis of evolutionarily divergent species highlights constraint on brain structure imposed by self-organizing neural networks. The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design.

Olfactory coding with patterns of response latencies.

The encoding of odors by spatiotemporal patterns of mitral/tufted (M/T) cells in the vertebrate olfactory bulb has been discussed controversially. Motivated by temporal constraints from behavioral studies, we investigated the information contained in odor-evoked first-spike latencies. Using simultaneous recordings of dozens of M/T cells with a high temporal resolution and quantitative ensemble correlation techniques, we show that latency patterns, and in particular latency rank patterns, are highly odor specific and reproducible. They reliably predict the odor identity as well as the odor concentration on a single-trial basis and on short timescales-in fact, more reliably than patterns of firing rates. Furthermore, we show that latency ranks exhibit a better reproducibility at the level of M/T cells than in olfactory receptor neurons. Our results suggest that the latency patterns of M/T cells contain all the information higher brain centers need to identify odors and their concentrations.

Dynamic effective connectivity of inter-areal brain circuits.

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities.

Coexistence of Regular and Irregular Dynamics in Complex Networks of Pulse-Coupled Oscillators

For general networks of pulse-coupled oscillators, including regular, random, and more complex networks, we develop an exact stability analysis of synchronous states. As opposed to conventional stability analysis, here stability is determined by a multitude of linear operators. We treat this multioperator problem exactly and show that for inhibitory interactions the synchronous state is stable, independent of the parameters and the network connectivity. In randomly connected networks with strong interactions this synchronous state, displaying regular dynamics, coexists with a balanced state exhibiting irregular dynamics. External signals may switch the network between qualitatively distinct states.

Complexin-I Is Required for High-Fidelity Transmission at the Endbulb of Held Auditory Synapse

Complexins (CPXs I–IV) presumably act as regulators of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex, but their function in the intact mammalian nervous system is not well established. Here, we explored the role of CPXs in the mouse auditory system. Hearing was impaired in CPX I knock-out mice but normal in knock-out mice for CPXs II, III, IV, and III/IV as measured by auditory brainstem responses. Complexins were not detectable in cochlear hair cells but CPX I was expressed in spiral ganglion neurons (SGNs) that give rise to the auditory nerve. Ca2+-dependent exocytosis of inner hair cells and sound encoding by SGNs were unaffected in CPX I knock-out mice. In the absence of CPX I, the resting release probability in the endbulb of Held synapses of the auditory nerve fibers with bushy cells in the cochlear nucleus was reduced. As predicted by computational modeling, bushy cells had decreased spike rates at sound onset as well as longer and more variable first spike latencies explaining the abnormal auditory brainstem responses. In addition, we found synaptic transmission to outlast the stimulus at many endbulb of Held synapses in vitro and in vivo, suggesting impaired synchronization of release to stimulus offset. Although sound encoding in the cochlea proceeds in the absence of complexins, CPX I is required for faithful processing of sound onset and offset in the cochlear nucleus.

Prevalence of Unstable Attractors in Networks of Pulse-Coupled Oscillators

We present and analyze the first example of a dynamical system that naturally exhibits attracting periodic orbits that are unstable. These unstable attractors occur in networks of pulse-coupled oscillators, and become prevalent with increasing network size for a wide range of parameters. They are enclosed by basins of attraction of other attractors but are remote from their own basin volume such that arbitrarily small noise leads to a switching among attractors.

Correlations and Synchrony in Threshold Neuron Models

We study how threshold models and neocortical neurons transfer temporal and interneuronal input correlations to correlations of spikes. In both, we find that the low common input regime is governed by firing rate dependent spike correlations which are sensitive to the detailed structure of input correlation functions. In the high common input regime, the spike correlations are largely insensitive to the firing rate and exhibit a universal peak shape. We further show that pairs with different firing rates driven by common inputs in general exhibit asymmetric spike correlations.