Dmitriy Aronov

Attractor dynamics of network UP states in the neocortex

The cerebral cortex receives input from lower brain regions, and its function is traditionally considered to be processing that input through successive stages to reach an appropriate output. However, the cortical circuit contains many interconnections, including those feeding back from higher centres, and is continuously active even in the absence of sensory inputs. Such spontaneous firing has a structure that reflects the coordinated activity of specific groups of neurons. Moreover, the membrane potential of cortical neurons fluctuates spontaneously between a resting (DOWN) and a depolarized (UP) state, which may also be coordinated. The elevated firing rate in the UP state follows sensory stimulation and provides a substrate for persistent activity, a network state that might mediate working memory. Using two-photon calcium imaging, we reconstructed the dynamics of spontaneous activity of up to 1,400 neurons in slices of mouse visual cortex. Here we report the occurrence of synchronized UP state transitions (‘cortical flashes’) that occur in spatially organized ensembles involving small numbers of neurons. Because of their stereotyped spatiotemporal dynamics, we conclude that network UP states are circuit attractors—emergent features of feedback neural networks that could implement memory states or solutions to computational problems.

A Specialized Forebrain Circuit for Vocal Babbling in the Juvenile Songbird

Young animals engage in variable exploratory behaviors essential for the development of neural circuitry and adult motor control, yet the neural basis of these behaviors is largely unknown. Juvenile songbirds produce subsong—a succession of primitive vocalizations akin to human babbling. We found that subsong production in zebra finches does not require HVC (high vocal center), a key premotor area for singing in adult birds, but does require LMAN (lateral magnocellular nucleus of the nidopallium), a forebrain nucleus involved in learning but not in adult singing. During babbling, neurons in LMAN exhibited premotor correlations to vocal output on a fast time scale. Thus, juvenile singing is driven by a circuit distinct from that which produces the adult behavior—a separation possibly general to other developing motor systems.

Calcium Microdomains in Aspiny Dendrites

Dendritic spines receive excitatory synapses and serve as calcium compartments, which appear to be necessary for input-specific synaptic plasticity. Dendrites of GABAergic interneurons have few or no spines and thus do not possess a clear morphological basis for synapse-specific compartmentalization. We demonstrate using two-photon calcium imaging that activation of single synapses on aspiny dendrites of neocortical fast spiking (FS) interneurons creates highly localized calcium microdomains, often restricted to less than 1 microm of dendritic space. We confirm using ultrastructural reconstruction of imaged dendrites the absence of any morphological basis for this compartmentalization and show that it is dependent on the fast kinetics of calcium-permeable (CP) AMPA receptors and fast local extrusion via the Na+/Ca2+ exchanger. Because aspiny dendrites throughout the CNS express CP-AMPA receptors, we propose that CP-AMPA receptors mediate a spine-free mechanism of input-specific calcium compartmentalization.

A Parturition-Associated Nonsynaptic Coherent Activity Pattern in the Developing Hippocampus

Correlated neuronal activity is instrumental in the formation of networks, but its emergence during maturation is poorly understood. We have used multibeam two-photon calcium microscopy combined with targeted electrophysiological recordings in order to determine the development of population coherence from embryonic to postnatal stages in the hippocampus. At embryonic stages (E16-E19), synchronized activity is absent, and neurons are intrinsically active and generate L-type channel-mediated calcium spikes. At birth, small cell assemblies coupled by gap junctions spontaneously generate synchronous nonsynaptic calcium plateaus associated to recurrent burst discharges. The emergence of coherent calcium plateaus at birth is controlled by oxytocin, a maternal hormone initiating labour, and progressively shut down a few days later by the synapse-driven giant depolarizing potentials (GDPs) that synchronize the entire network. Therefore, in the developing hippocampus, delivery is an important signal that triggers the first coherent activity pattern, which is silenced by the emergence of synaptic transmission.

Changes in the neural control of a complex motor sequence during learning

The acquisition of complex motor sequences often proceeds through trial-and-error learning, requiring the deliberate exploration of motor actions and the concomitant evaluation of the resulting performance. Songbirds learn their song in this manner, producing highly variable vocalizations as juveniles. As the song improves, vocal variability is gradually reduced until it is all but eliminated in adult birds. In the present study we examine how the motor program underlying such a complex motor behavior evolves during learning by recording from the robust nucleus of the arcopallium (RA), a motor cortex analog brain region. In young birds, neurons in RA exhibited highly variable firing patterns that throughout development became more precise, sparse, and bursty. We further explored how the developing motor program in RA is shaped by its two main inputs: LMAN, the output nucleus of a basal ganglia-forebrain circuit, and HVC, a premotor nucleus. Pharmacological inactivation of LMAN during singing made the song-aligned firing patterns of RA neurons adultlike in their stereotypy without dramatically affecting the spike statistics or the overall firing patterns. Removing the input from HVC, on the other hand, resulted in a complete loss of stereotypy of both the song and the underlying motor program. Thus our results show that a basal ganglia-forebrain circuit drives motor exploration required for trial-and-error learning by adding variability to the developing motor program. As learning proceeds and the motor circuits mature, the relative contribution of LMAN is reduced, allowing the premotor input from HVC to drive an increasingly stereotyped song.

Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system.

Virtual reality (VR) enables precise control of an animals environment and otherwise impossible experimental manipulations. Neural activity in rodents has been studied on virtual 1D tracks. However, 2D navigation imposes additional requirements, such as the processing of head direction and environment boundaries, and it is unknown whether the neural circuits underlying 2D representations can be sufficiently engaged in VR. We implemented a VR setup for rats, including software and large-scale electrophysiology, that supports 2D navigation by allowing rotation and walking in any direction. The entorhinal-hippocampal circuit, including place, head direction, and grid cells, showed 2D activity patterns similar to those in the real world. Furthermore, border cells were observed, and hippocampal remapping was driven by environment shape, suggesting functional processing of virtual boundaries. These results illustrate that 2D spatial representations can be engaged by visual and rotational vestibular stimuli alone and suggest a novel VR tool for studying rat navigation.

Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit

During spatial navigation, neural activity in the hippocampus and the medial entorhinal cortex (MEC) is correlated to navigational variables such as location, head direction, speed, and proximity to boundaries. These activity patterns are thought to provide a map-like representation of physical space. However, the hippocampal–entorhinal circuit is involved not only in spatial navigation, but also in a variety of memory-guided behaviours. The relationship between this general function and the specialized spatial activity patterns is unclear. A conceptual framework reconciling these views is that spatial representation is just one example of a more general mechanism for encoding continuous, task-relevant variables. Here we tested this idea by recording from hippocampal and entorhinal neurons during a task that required rats to use a joystick to manipulate sound along a continuous frequency axis. We found neural representation of the entire behavioural task, including activity that formed discrete firing fields at particular sound frequencies. Neurons involved in this representation overlapped with the known spatial cell types in the circuit, such as place cells and grid cells. These results suggest that common circuit mechanisms in the hippocampal–entorhinal system are used to represent diverse behavioural tasks, possibly supporting cognitive processes beyond spatial navigation.

Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons.

Spike train metrics quantify the notion of dissimilarity, or distance, between spike trains and between multineuronal responses (J. Neurophysiol. 76 (1996) 1310, Network 8 (1997) 127). We present a new algorithm for the implementation of a metric based on the timing of individual spikes and on their neurons of origin. This algorithm surpasses the earlier approach in speed by a factor that grows exponentially with the number of neurons, substantially extending the applicability of metric space methods to the study of coding in larger neuronal populations.

Two Distinct Modes of Forebrain Circuit Dynamics Underlie Temporal Patterning in the Vocalizations of Young Songbirds

Accurate timing is a critical aspect of motor control, yet the temporal structure of many mature behaviors emerges during learning from highly variable exploratory actions. How does a developing brain acquire the precise control of timing in behavioral sequences? To investigate the development of timing, we analyzed the songs of young juvenile zebra finches. These highly variable vocalizations, akin to human babbling, gradually develop into temporally stereotyped adult songs. We find that the durations of syllables and silences in juvenile singing are formed by a mixture of two distinct modes of timing: a random mode producing broadly distributed durations early in development, and a stereotyped mode underlying the gradual emergence of stereotyped durations. Using lesions, inactivations, and localized brain cooling, we investigated the roles of neural dynamics within two premotor cortical areas in the production of these temporal modes. We find that LMAN (lateral magnocellular nucleus of the nidopallium) is required specifically for the generation of the random mode of timing and that mild cooling of LMAN causes an increase in the durations produced by this mode. On the contrary, HVC (used as a proper name) is required specifically for producing the stereotyped mode of timing, and its cooling causes a slowing of all stereotyped components. These results show that two neural pathways contribute to the timing of juvenile songs and suggest an interesting organization in the forebrain, whereby different brain areas are specialized for the production of distinct forms of neural dynamics.

Natural Changes in Brain Temperature Underlie Variations in Song Tempo during a Mating Behavior

The song of a male zebra finch is a stereotyped motor sequence whose tempo varies with social context – whether or not the song is directed at a female bird – as well as with the time of day. The neural mechanisms underlying these changes in tempo are unknown. Here we show that brain temperature recorded in freely behaving male finches exhibits a global increase in response to the presentation of a female bird. This increase strongly correlates with, and largely explains, the faster tempo of songs directed at a female compared to songs produced in social isolation. Furthermore, we find that the observed diurnal variations in song tempo are also explained by natural variations in brain temperature. Our findings suggest that brain temperature is an important variable that can influence the dynamics of activity in neural circuits, as well as the temporal features of behaviors that some of these circuits generate.