Top-Down Suppression of Sensory Cortex in an NMDAR Hypofunction Model of Psychosis.

Conceptual and computational models have been advanced that propose that perceptual disturbances in psychosis, such as hallucinations, may arise due to a disruption in the balance between bottom-up (ie sensory) and top-down (ie from higher brain areas) information streams in sensory cortex. However, the neural activity underlying this hypothesized alteration remains largely unexplored. Pharmacological N-methyl-d-aspartate receptor (NMDAR) antagonism presents an attractive model to examine potential changes as it acutely recapitulates many of the symptoms of schizophrenia including hallucinations, and NMDAR hypofunction is strongly implicated in the pathogenesis of schizophrenia as evidenced by large-scale genetic studies. Here we use in vivo 2-photon imaging to measure frontal top-down signals from the anterior cingulate cortex (ACC) and their influence on activity of the primary visual cortex (V1) in mice during pharmacologically induced NMDAR hypofunction. We find that global NMDAR hypofunction causes a significant increase in activation of top-down ACC axons, and that surprisingly this is associated with an ACC-dependent net suppression of spontaneous activity in V1 as well as a reduction in V1 sensory-evoked activity. These findings are consistent with a model in which perceptual disturbances in psychosis are caused in part by aberrant top-down frontal cortex activity that suppresses the transmission of sensory signals through early sensory areas.

Active properties of neocortical pyramidal neuron dendrites.

Dendrites are the main recipients of synaptic inputs and are important sites that determine neurons' input-output functions. This review focuses on thin neocortical dendrites, which receive the vast majority of synaptic inputs in cortex but also have specialized electrogenic properties. We present a simplified working-model biophysical scheme of pyramidal neurons that attempts to capture the essence of their dendritic function, including the ability to behave under plausible conditions as dynamic computational subunits. We emphasize the electrogenic capabilities of NMDA receptors (NMDARs) because these transmitter-gated channels seem to provide the major nonlinear depolarizing drive in thin dendrites, even allowing full-blown NMDA spikes. We show how apparent discrepancies in experimental findings can be reconciled and discuss the current status of dendritic spikes in vivo; a dominant NMDAR contribution would indicate that the input-output relations of thin dendrites are dynamically set by network activity and cannot be fully predicted by purely reductionist approaches.

NMDA and GABAB (KIR) conductances: the "perfect couple" for bistability.

Networks that produce persistent firing in response to novel input patterns are thought to be important in working memory and other information storage functions. One possible mechanism for maintaining persistent firing is dendritic voltage bistability in which the depolarized state depends on the voltage dependence of the NMDA conductance at recurrent synapses. In previous models, the hyperpolarized state is dependent on voltage-independent conductances, including GABA(A). The interplay of these conductances leads to bistability, but its robustness is limited by the fact that the conductance ratio must be within a narrow range. The GABA(B) component of inhibitory transmission was not considered in previous analyses. Here, we show that the voltage dependence of the inwardly rectifying potassium (KIR) conductance activated by GABA(B) receptors adds substantial robustness to network simulations of bistability and the persistent firing that it underlies. The hyperpolarized state is robust because, at hyperpolarized potentials, the GABA(B)/KIR conductance is high and the NMDA conductance is low; the depolarized state is robust because, at depolarized potentials, the NMDA conductance is high and the GABA(B)/KIR conductance is low. Our results suggest that this complementary voltage dependence of GABA(B)/KIR and NMDA conductances makes them a "perfect couple" for producing voltage bistability.

Spatiotemporally graded NMDA spike/plateau potentials in basal dendrites of neocortical pyramidal neurons.

Glutamatergic inputs clustered over approximately 20-40 microm can elicit local N-methyl-D-aspartate (NMDA) spike/plateau potentials in terminal dendrites of cortical pyramidal neurons, inspiring the notion that a single terminal dendrite can function as a decision-making computational subunit. A typical terminal basal dendrite is approximately 100-200 microm long: could it function as multiple decision-making subunits? We test this by sequential focal stimulation of multiple sites along terminal basal dendrites of layer 5 pyramidal neurons in rat somatosensory cortical brain slices, using iontophoresis or uncaging of brief glutamate pulses. There was an approximately sevenfold spatial gradient in average spike/plateau amplitude measured at the soma, from approximately 3 mV for distal inputs to approximately 23 mV for proximal inputs. Spike/plateaus were NMDA receptor (NMDAR) conductance-dominated at all locations. Large Ca(2+) transients accompanied spike/plateaus over a approximately 10- to 40-microm zone around the input site; smaller Ca(2+) transients extended approximately uniformly to the dendritic tip. Spike/plateau duration grew with increasing glutamate and depolarization; high Ca(2+) zone size grew with spike/plateau duration. The minimum high Ca(2+) zone half-width (just above NMDA spike threshold) increased from distal (approximately 10 microm) to proximal locations (approximately 25 microm), as did the NMDA spike glutamate threshold. Depolarization reduced glutamate thresholds. Simulations exploring multi-site interactions based on this demonstrate that if appropriately timed and localized inputs occur in vivo, a single basal dendrite could correspond to a cascade of multiple co-operating dynamic decision-making subunits able to retain information for hundreds of milliseconds, with increasing influence on neural output from distal to proximal. Dendritic NMDA spike/plateaus are thus well-suited to support graded persistent firing.

Persistent neural activity: prevalence and mechanisms.

Persistent neural activity refers to a sustained change in action potential discharge that long outlasts a stimulus. It is found in a diverse set of brain regions and organisms and several in vitro systems, suggesting that it can be considered a universal form of circuit dynamics that can be used as a mechanism for short-term storage and accumulation of sensory or motor information. Both single cell and network mechanisms are likely to co-operate in generating persistent activity in many brain areas.

Plasticity and tuning of the time course of analog persistent firing in a neural integrator.

In a companion paper, we reported that the goldfish oculomotor neural integrator could be trained to instability or leak by rotating the visual surround with a velocity proportional to +/- horizontal eye position, respectively. Here we analyze changes in the firing rate behavior of neurons in area I in the caudal brainstem, a central component of the oculomotor neural integrator. Persistent firing could be detuned to instability and leak, respectively, along with fixation behavior. Prolonged training could reduce the time constant of persistent firing of some cells by more than an order of magnitude, to <1 s. Normal visual feedback gradually retuned persistent firing of integrator neurons toward stability, along with fixation behavior. In animals with unstable fixations, approximately half of the eye position-related cells had upward or unstable firing rate drift. In animals with leaky fixations, two-thirds of the eye position-related cells showed leaky firing drift. The remaining eye position-related cells, generally those with lower eye position thresholds, showed a more complex pattern of history-dependent/predictive firing rate drift in relation to eye drift. These complex drift cells often showed a drop in maximum persistent firing rate after training to leak. Despite this diversity, firing drift and the degree of instability or leak in firing rates were broadly correlated with fixation performance. The presence, strength, and reversibility of this plasticity demonstrate that, in this system, visual feedback plays a vital role in gradually tuning the time course of persistent neural firing.

Plasticity and tuning by visual feedback of the stability of a neural integrator.

Persistent neural firing is of fundamental importance to working memory and other brain functions because it allows information to be held "online" following an input and to be integrated over time. Many models of persistent activity rely on some kind of positive feedback internal to the neural circuit concerned; however, too much feedback causes runaway firing (instability), and too little results in loss of persistence (leak). This parameter sensitivity leads to the hypothesis that the brain uses an error signal (external feedback) to tune the stability of persistent firing by adjusting the amount of internal feedback. We test this hypothesis by manipulating external visual feedback, a putative sensory error signal, in a model system for persistent firing, the goldfish oculomotor neural integrator. Over tens of minutes to hours, electronically controlled visual feedback consistent with a leaky or unstable integrator can drive the integrator progressively more unstable or leaky, respectively. Eye fixation time constants can be reduced >100-fold to <1 s. Normal visual feedback gradually retunes the integrator back to stability. Changes in the phase of the sinusoidal vestibulo-ocular response are consistent with integrator detuning, as are changes in ocular drift following eye position shifts compensating for brief passive head movements during fixations. Corresponding changes in persistent firing of integrator neurons are presented in the accompanying article. The presence, strength, and reversibility of the plasticity demonstrate that, in this system, external visual feedback plays a vital role in gradually tuning the stability of the neural integrator.

History dependence of rate covariation between neurons during persistent activity in an oculomotor integrator.

Persistent firing in response to a brief stimulus is a neural correlate of short-term memory in a variety of systems. In the oculomotor neural integrator, persistent firing that encodes eye position is maintained in response to transient saccadic eye-velocity commands. To a first approximation, firing rates in the integrator vary linearly with eye position. Thus, viewed across many cells, the pattern of persistent firing in the integrator may be constrained to a unique line of stable states. Here this idea was tested by examining the relationship between firing rates of simultaneously recorded neurons. Paired recordings were obtained in awake goldfish from neurons in hindbrain area I, an essential part of the horizontal eye-position integrator. During spontaneous eye movements consisting of sequential fixations at different horizontal positions, the pair relationship between the majority of cells on the same side of the integrator was not unique: for a given rate of one cell, the rate of the paired cell assumed different values that depended systematically on the preceding saccade history. This finding suggests that the set of persistent firing states that encode eye position is not constrained to a unique line, and that models with stable states restricted to a such a line need to be modified accordingly.

Robust persistent neural activity in a model integrator with multiple hysteretic dendrites per neuron.

Short-term memory is often correlated with persistent changes in neuronal firing rates in response to transient inputs. We model the persistent maintenance of an analog eye position signal by an oculomotor neural integrator receiving transient eye movement commands. Previous models of this network rely on precisely tuned positive feedback with <1% tolerance to mistuning, or use neurons that exhibit large discontinuities in firing rate with small changes in eye position. We show analytically how using neurons with multiple bistable dendritic compartments can enhance the robustness of eye fixations to mistuning while reproducing the approximately linear and continuous relationship between neuronal firing rates and eye position, and the dependence of neuron pair firing rate relationships on the direction of the previous saccade. The response of the model to continuously varying inputs makes testable predictions for the performance of the vestibuloocular reflex. Our results suggest that dendritic bistability could stabilize the persistent neural activity observed in working memory systems.

Linear regression of eye velocity on eye position and head velocity suggests a common oculomotor neural integrator.

The oculomotor system produces eye-position signals during fixations and head movements by integrating velocity-coded saccadic and vestibular inputs. A previous analysis of nucleus prepositus hypoglossi (nph) lesions in monkeys found that the integration time constant for maintaining fixations decreased, while that for the vestibulo-ocular reflex (VOR) did not. On this basis, it was concluded that saccadic inputs are integrated by the nph, but that the vestibular inputs are integrated elsewhere. We re-analyze the data from which this conclusion was drawn by performing a linear regression of eye velocity on eye position and head velocity to derive the time constant and velocity bias of an imperfect oculomotor neural integrator. The velocity-position regression procedure reveals that the integration time constants for both VOR and saccades decrease in tandem with consecutive nph lesions, consistent with the hypothesis of a single common integrator. The previous evaluation of the integrator time constant relied upon fitting methods that are prone to error in the presence of velocity bias and saccades. The algorithm used to evaluate imperfect fixations in the dark did not account for the nonzero null position of the eyes associated with velocity bias. The phase-shift analysis used in evaluating the response to sinusoidal vestibular input neglects the effect of saccadic resets of eye position on intersaccadic eye velocity, resulting in gross underestimates of the imperfections in integration during VOR. The linear regression method presented here is valid for both fixation and low head velocity VOR data and is easy to implement.