How do neurons work together? Lessons from auditory cortex.

Recordings of single neurons have yielded great insights into the way acoustic stimuli are represented in auditory cortex. However, any one neuron functions as part of a population whose combined activity underlies cortical information processing. Here we review some results obtained by recording simultaneously from auditory cortical populations and individual morphologically identified neurons, in urethane-anesthetized and unanesthetized passively listening rats. Auditory cortical populations produced structured activity patterns both in response to acoustic stimuli, and spontaneously without sensory input. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events, exhibiting a generally conserved sequential organization lasting approximately 100 ms. Both spontaneous and evoked events exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, and densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. Laminar propagation differed however, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. In both unanesthetized and urethanized rats, global activity fluctuated between "desynchronized" state characterized by low amplitude, high-frequency local field potentials and a "synchronized" state of larger, lower-frequency waves. Computational studies suggested that responses could be predicted by a simple dynamical system model fitted to the spontaneous activity immediately preceding stimulus presentation. Fitting this model to the data yielded a nonlinear self-exciting system model in synchronized states and an approximately linear system in desynchronized states. We comment on the significance of these results for auditory cortical processing of acoustic and non-acoustic information.

The asynchronous state in cortical circuits.

Correlated spiking is often observed in cortical circuits, but its functional role is controversial. It is believed that correlations are a consequence of shared inputs between nearby neurons and could severely constrain information decoding. Here we show theoretically that recurrent neural networks can generate an asynchronous state characterized by arbitrarily low mean spiking correlations despite substantial amounts of shared input. In this state, spontaneous fluctuations in the activity of excitatory and inhibitory populations accurately track each other, generating negative correlations in synaptic currents which cancel the effect of shared input. Near-zero mean correlations were seen experimentally in recordings from rodent neocortex in vivo. Our results suggest a reexamination of the sources underlying observed correlations and their functional consequences for information processing.

High-resolution in vivo imaging of the neurovascular unit during spreading depression.

Spreading depression (SD) is a propagating wave of neuronal depolarization and ionic shifts, seen in stroke and migraine. In vitro, SD is associated with astrocytic [Ca2+] waves, but it is unclear what role they play and whether they influence cerebral blood flow, which is altered in SD. Here we show that SD in vivo is associated with [Ca2+] waves in astrocytes and neurons and with constriction of intracortical arterioles severe enough to result in arrest of capillary perfusion. The vasoconstriction is correlated with fast astrocytic [Ca2+] waves and is inhibited when they are reduced. [Ca2+] waves appear in neurons before astrocytes, and inhibition of astrocytic [Ca2+] waves does not depress SD propagation. This suggests that astrocytes do not drive SD propagation but are responsible for the hemodynamic failure seen deep in the cortex. Similar waves occur in anoxic depolarizations (AD), supporting the notion that SD and AD are related processes.