Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.

Sequential neural activity patterns are as ubiquitous as the outputs they drive, which include motor gestures and sequential cognitive processes. Neural sequences are long, compared to the activation durations of participating neurons, and sequence coding is sparse. Numerous studies demonstrate that spike-time-dependent plasticity (STDP), the primary known mechanism for temporal order learning in neurons, cannot organize networks to generate long sequences, raising the question of how such networks are formed. We show that heterosynaptic competition within single neurons, when combined with STDP, organizes networks to generate long unary activity sequences even without sequential training inputs. The network produces a diversity of sequences with a power law length distribution and exponent -1, independent of cellular time constants. We show evidence for a similar distribution of sequence lengths in the recorded premotor song activity of songbirds. These results suggest that neural sequences may be shaped by synaptic constraints and network circuitry rather than cellular time constants.

Rapid interhemispheric switching during vocal production in a songbird.

To generate complex bilateral motor patterns such as those underlying birdsong, neural activity must be highly coordinated across the two cerebral hemispheres. However, it remains largely elusive how this coordination is achieved given that interhemispheric communication between song-control areas in the avian cerebrum is restricted to projections received from bilaterally connecting areas in the mid- and hindbrain. By electrically stimulating cerebral premotor areas in zebra finches, we find that behavioral effectiveness of stimulation rapidly switches between hemispheres. In time intervals in which stimulation in one hemisphere tends to distort songs, stimulation in the other hemisphere is mostly ineffective, revealing an idiosyncratic form of motor dominance that bounces back and forth between hemispheres like a virtual ping-pong ball. The intervals of lateralized effectiveness are broadly distributed and are unrelated to simple spectral and temporal song features. Such interhemispheric switching could be an important dynamical aspect of neural coordination that may have evolved from simpler pattern generator circuits.

Spikes and bursts in two types of thalamic projection neurons differentially shape sleep patterns and auditory responses in a songbird.

In mammals, the thalamus plays important roles for cortical processing, such as relay of sensory information and induction of rhythmical firing during sleep. In neurons of the avian cerebrum, in analogy with cortical up and down states, complex patterns of regular-spiking and dense-bursting modes are frequently observed during sleep. However, the roles of thalamic inputs for shaping these firing modes are largely unknown. A suspected key player is the avian thalamic nucleus uvaeformis (Uva). Uva is innervated by polysensory input, receives indirect cerebral feedback via the midbrain, and projects to the cerebrum via two distinct pathways. Using pharmacological manipulation, electrical stimulation, and extracellular recordings of Uva projection neurons, we study the involvement of Uva in zebra finches for the generation of spontaneous activity and auditory responses in premotor area HVC (used as a proper name) and the downstream robust nucleus of the arcopallium (RA). In awake and sleeping birds, we find that single Uva spikes suppress and spike bursts enhance spontaneous and auditory-evoked bursts in HVC and RA neurons. Strong burst suppression is mediated mainly via tonically firing HVC-projecting Uva neurons, whereas a fast burst drive is mediated indirectly via Uva neurons projecting to the nucleus interface of the nidopallium. Our results reveal that cerebral sleep-burst epochs and arousal-related burst suppression are both shaped by sophisticated polysynaptic thalamic mechanisms.