Population rate dynamics and multineuron firing patterns in sensory cortex.

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron "words" (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features.

State-dependent representation of amplitude-modulated noise stimuli in rat auditory cortex.

Cortical responses can vary greatly between repeated presentations of an identical stimulus. Here we report that both trial-to-trial variability and faithfulness of auditory cortical stimulus representations depend critically on brain state. A frozen amplitude-modulated white noise stimulus was repeatedly presented while recording neuronal populations and local field potentials (LFPs) in auditory cortex of urethane-anesthetized rats. An information-theoretic measure was used to predict neuronal spiking activity from either the stimulus envelope or simultaneously recorded LFP. Evoked LFPs and spiking more faithfully followed high-frequency temporal modulations when the cortex was in a desynchronized state. In the synchronized state, neural activity was poorly predictable from the stimulus envelope, but the spiking of individual neurons could still be predicted from the ongoing LFP. Our results suggest that although auditory cortical activity remains coordinated as a population in the synchronized state, the ability of continuous auditory stimuli to control this activity is greatly diminished.

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.

Population coding of tone stimuli in auditory cortex: dynamic rate vector analysis.

Neural representations of even temporally unstructured stimuli can show complex temporal dynamics. In many systems, neuronal population codes show 'progressive differentiation', whereby population responses to different stimuli grow further apart during a stimulus presentation. Here we analysed the response of auditory cortical populations in rats to extended tones. At onset (up to 300 ms), tone responses involved strong excitation of a large number of neurons; during sustained responses (after 500 ms) overall firing rate decreased, but most cells still showed statistically significant rate modulation. Population vector trajectories evoked by different tone frequencies expanded rapidly along an initially similar trajectory in the first tens of milliseconds after tone onset, later diverging to smaller amplitude fixed points corresponding to sustained responses. The angular difference between onset and sustained responses to the same tone was greater than between different tones in the same stimulus epoch. No clear orthogonalization of responses was found with time, and predictability of the stimulus from population activity also decreased during this period compared with onset. The question of whether population activity grew more or less sparse with time depended on the precise mathematical sense given to this term. We conclude that auditory cortical population responses to tones differ from those reported in many other systems, with progressive differentiation not seen for sustained stimuli. Sustained acoustic stimuli are typically not behaviorally salient: we hypothesize that the dynamics we observe may instead allow an animal to maintain a representation of such sounds, at low energetic cost.

Sequential structure of neocortical spontaneous activity in vivo.

Even in the absence of sensory stimulation, the neocortex shows complex spontaneous activity patterns, often consisting of alternating "DOWN" states of generalized neural silence and "UP" states of massive, persistent network activity. To investigate how this spontaneous activity propagates through neuronal assemblies in vivo, we simultaneously recorded populations of 50-200 cortical neurons in layer V of anesthetized and awake rats. Each neuron displayed a virtually unique spike pattern during UP states, with diversity seen amongst both putative pyramidal cells and interneurons, reflecting a complex but stereotypically organized sequential spread of activation through local cortical networks. Spike timing was most precise during the first approximately 100 ms after UP state onset, and decayed as UP states progressed. A subset of UP states propagated as traveling waves, but waves passing a given point in either direction initiated similar local sequences, suggesting local networks as the substrate of sequential firing patterns. A search for repeating motifs indicated that their occurrence and structure was predictable from neurons' individual latencies to UP state onset. We suggest that these stereotyped patterns arise from the interplay of intrinsic cellular conductances and local circuit properties.