Equalizing excitation-inhibition ratios across visual cortical neurons.

The relationship between synaptic excitation and inhibition (E/I ratio), two opposing forces in the mammalian cerebral cortex, affects many cortical functions such as feature selectivity and gain. Individual pyramidal cells show stable E/I ratios in time despite fluctuating cortical activity levels. This is because when excitation increases, inhibition increases proportionally through the increased recruitment of inhibitory neurons, a phenomenon referred to as excitation-inhibition balance. However, little is known about the distribution of E/I ratios across pyramidal cells. Through their highly divergent axons, inhibitory neurons indiscriminately contact most neighbouring pyramidal cells. Is inhibition homogeneously distributed or is it individually matched to the different amounts of excitation received by distinct pyramidal cells? Here we discover that pyramidal cells in layer 2/3 of mouse primary visual cortex each receive inhibition in a similar proportion to their excitation. As a consequence, E/I ratios are equalized across pyramidal cells. This matched inhibition is mediated by parvalbumin-expressing but not somatostatin-expressing inhibitory cells and results from the independent adjustment of synapses originating from individual parvalbumin-expressing cells targeting different pyramidal cells. Furthermore, this match is activity-dependent as it is disrupted by perturbing pyramidal cell activity. Thus, the equalization of E/I ratios across pyramidal cells reveals an unexpected degree of order in the spatial distribution of synaptic strengths and indicates that the relationship between the cortex's two opposing forces is stabilized not only in time but also in space.

Efficient coding of cognitive variables underlies dopamine response and choice behavior.

Reward expectations based on internal knowledge of the external environment are a core component of adaptive behavior. However, internal knowledge may be inaccurate or incomplete due to errors in sensory measurements. Some features of the environment may also be encoded inaccurately to minimize representational costs associated with their processing. In this study, we investigated how reward expectations are affected by features of internal representations by studying behavior and dopaminergic activity while mice make time-based decisions. We show that several possible representations allow a reinforcement learning agent to model animals' overall performance during the task. However, only a small subset of highly compressed representations simultaneously reproduced the co-variability in animals' choice behavior and dopaminergic activity. Strikingly, these representations predict an unusual distribution of response times that closely match animals' behavior. These results inform how constraints of representational efficiency may be expressed in encoding representations of dynamic cognitive variables used for reward-based computations.

Supralinear increase of recurrent inhibition during sparse activity in the somatosensory cortex.

The balance between excitation and inhibition in the cortex is crucial in determining sensory processing. Because the amount of excitation varies, maintaining this balance is a dynamic process; yet the underlying mechanisms are poorly understood. We show here that the activity of even a single layer 2/3 pyramidal cell in the somatosensory cortex of the rat generates widespread inhibition that increases disproportionately with the number of active pyramidal neurons. This supralinear increase of inhibition results from the incremental recruitment of somatostatin-expressing inhibitory interneurons located in layers 2/3 and 5. The recruitment of these interneurons increases tenfold when they are excited by two pyramidal cells. A simple model demonstrates that the distribution of excitatory input amplitudes onto inhibitory neurons influences the sensitivity and dynamic range of the recurrent circuit. These data show that through a highly sensitive recurrent inhibitory circuit, cortical excitability can be modulated by one pyramidal cell.

Complementary modulation of somatic inhibition by opioids and cannabinoids.

Somatic inhibition, which is critical for determining the spike output of principal cells, is mediated by two physiologically distinct classes of GABAergic interneurons called basket cells. In the hippocampus, despite both targeting the somatic membrane of CA1 pyramidal cells, these two classes of basket cells are active at different times. Differential modulation of these two types of basket cells could hence be important for regulating the activity patterns of CA1 pyramidal cells at very specific periods during ongoing activity. Indeed, cannabinoids selectively suppress the output of one class of basket cell. Whether opioids, another major modulator of inhibition in the hippocampus, also selectively suppress somatic inhibition is not known. Here, we show that basket cells are selectively modulated by either opioids or cannabinoids, but not both. We also find that basket cells are integrated into specific inhibitory subnetworks that are themselves under differential control of opioids and cannabinoids. Furthermore, because the two interneuron types are activated at different times, opioids and cannabinoids suppress different epochs of inhibition. This cell-type specific sensitivity to neuromodulators allows for a fine control of the temporal structure of hippocampal activity.

Midbrain dopamine neurons control judgment of time.

Our sense of time is far from constant. For instance, time flies when we are having fun, and it slows to a trickle when we are bored. Midbrain dopamine neurons have been implicated in variable time estimation. However, a direct link between signals carried by dopamine neurons and temporal judgments is lacking. We measured and manipulated the activity of dopamine neurons as mice judged the duration of time intervals. We found that pharmacogenetic suppression of dopamine neurons decreased behavioral sensitivity to time and that dopamine neurons encoded information about trial-to-trial variability in time estimates. Last, we found that transient activation or inhibition of dopamine neurons was sufficient to slow down or speed up time estimation, respectively. Dopamine neuron activity thus reflects and can directly control the judgment of time.

Bonsai: an event-based framework for processing and controlling data streams.

The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for the acquisition and online processing of data streams. We describe Bonsai's core principles and architecture and demonstrate how it allows for the rapid and flexible prototyping of integrated experimental designs in neuroscience. We specifically highlight some applications that require the combination of many different hardware and software components, including video tracking of behavior, electrophysiology and closed-loop control of stimulation.

Ongoing behavior predicts perceptual report of interval duration.

The ability to estimate the passage of time is essential for adaptive behavior in complex environments. Yet, it is not known how the brain encodes time over the durations necessary to explain animal behavior. Under temporally structured reinforcement schedules, animals tend to develop temporally structured behavior, and interval timing has been suggested to be accomplished by learning sequences of behavioral states. If this is true, trial to trial fluctuations in behavioral sequences should be predictive of fluctuations in time estimation. We trained rodents in an duration categorization task while continuously monitoring their behavior with a high speed camera. Animals developed highly reproducible behavioral sequences during the interval being timed. Moreover, those sequences were often predictive of perceptual report from early in the trial, providing support to the idea that animals may use learned behavioral patterns to estimate the duration of time intervals. To better resolve the issue, we propose that continuous and simultaneous behavioral and neural monitoring will enable identification of neural activity related to time perception that is not explained by ongoing behavior.

Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli.

The response of cortical neurons to a sensory stimulus is shaped by the network in which they are embedded. Here we establish a role of parvalbumin (PV)-expressing cells, a large class of inhibitory neurons that target the soma and perisomatic compartments of pyramidal cells, in controlling cortical responses. By bidirectionally manipulating PV cell activity in visual cortex we show that these neurons strongly modulate layer 2/3 pyramidal cell spiking responses to visual stimuli while only modestly affecting their tuning properties. PV cells' impact on pyramidal cells is captured by a linear transformation, both additive and multiplicative, with a threshold. These results indicate that PV cells are ideally suited to modulate cortical gain and establish a causal relationship between a select neuron type and specific computations performed by the cortex during sensory processing.

Rapid target-specific remodeling of fast-spiking inhibitory circuits after loss of dopamine.

In Parkinson's disease (PD), dopamine depletion alters neuronal activity in the direct and indirect pathways and leads to increased synchrony in the basal ganglia network. However, the origins of these changes remain elusive. Because GABAergic interneurons regulate activity of projection neurons and promote neuronal synchrony, we recorded from pairs of striatal fast-spiking (FS) interneurons and direct- or indirect-pathway MSNs after dopamine depletion with 6-OHDA. Synaptic properties of FS-MSN connections remained similar, yet within 3 days of dopamine depletion, individual FS cells doubled their connectivity to indirect-pathway MSNs, whereas connections to direct-pathway MSNs remained unchanged. A model of the striatal microcircuit revealed that such increases in FS innervation were effective at enhancing synchrony within targeted cell populations. These data suggest that after dopamine depletion, rapid target-specific microcircuit organization in the striatum may lead to increased synchrony of indirect-pathway MSNs that contributes to pathological network oscillations and motor symptoms of PD.

Instantaneous modulation of gamma oscillation frequency by balancing excitation with inhibition.

Neurons recruited for local computations exhibit rhythmic activity at gamma frequencies. The amplitude and frequency of these oscillations are continuously modulated depending on stimulus and behavioral state. This modulation is believed to crucially control information flow across cortical areas. Here we report that in the rat hippocampus gamma oscillation amplitude and frequency vary rapidly, from one cycle to the next. Strikingly, the amplitude of one oscillation predicts the interval to the next. Using in vivo and in vitro whole-cell recordings, we identify the underlying mechanism. We show that cycle-by-cycle fluctuations in amplitude reflect changes in synaptic excitation spanning over an order of magnitude. Despite these rapid variations, synaptic excitation is immediately and proportionally counterbalanced by inhibition. These rapid adjustments in inhibition instantaneously modulate oscillation frequency. So, by rapidly balancing excitation with inhibition, the hippocampal network is able to swiftly modulate gamma oscillations over a wide band of frequencies.

Input normalization by global feedforward inhibition expands cortical dynamic range.

The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mechanisms that enable this wide range of operation are not fully understood. We found that the amplitude of excitatory synaptic currents necessary to fire rodent pyramidal cells, the threshold excitatory current, increased with stimulus strength. Consequently, the relative contribution of individual afferents in firing a neuron was inversely proportional to the total number of active afferents. Feedforward inhibition, acting homogeneously across pyramidal cells, ensured that threshold excitatory currents increased with stimulus strength. In contrast, heterogeneities in the distribution of excitatory currents in the neuronal population determined the specific set of pyramidal cells recruited. Together, these mechanisms expand the range of afferent input strengths that neuronal populations can represent.