Neuromodulatory control of localized dendritic spiking in critical period cortex.

Sensory experience in early postnatal life, during so-called critical periods, restructures neural circuitry to enhance information processing1. Why the cortex is susceptible to sensory instruction in early life and why this susceptibility wanes with age are unclear. Here we define a developmentally restricted engagement of inhibitory circuitry that shapes localized dendritic activity and is needed for vision to drive the emergence of binocular visual responses in the mouse primary visual cortex. We find that at the peak of the critical period for binocular plasticity, acetylcholine released from the basal forebrain during periods of heightened arousal directly excites somatostatin (SST)-expressing interneurons. Their inhibition of pyramidal cell dendrites and of fast-spiking, parvalbumin-expressing interneurons enhances branch-specific dendritic responses and somatic spike rates within pyramidal cells. By adulthood, this cholinergic sensitivity is lost, and compartmentalized dendritic responses are absent but can be re-instated by optogenetic activation of SST cells. Conversely, suppressing SST cell activity during the critical period prevents the normal development of binocular receptive fields by impairing the maturation of ipsilateral eye inputs. This transient cholinergic modulation of SST cells, therefore, seems to orchestrate two features of neural plasticity-somatic disinhibition and compartmentalized dendritic spiking. Loss of this modulation may contribute to critical period closure

When your eyes see more than you do

SummaryVisual information is used by the brain to construct a conscious experience of the visual world and to guide motor actions [1]. Here we report a study of how eye movements and perception relate to each other. We compared the ability of human observers to perceive image motion with the reliability of their eyes to track the motion of a target [2–4], the goal being to test whether both motor and sensory processes are based on the same set of signals and limited by a shared source of noise [2,4]. We found that the oculomotor system can detect fluctuations in the velocity of a moving target better than the observer. Surprisingly, in some conditions, eye movements reliably respond to the velocity fluctuations of a moving target that are otherwise perceptually invisible to the subjects. The implication is that visual motion signals exist in the brain that can be used to guide motor actions without evoking a perceptual outcome nor being accessible to conscious scrutiny

State-Dependent Subnetworks of Parvalbumin-Expressing Interneurons in Neocortex.

Brain state determines patterns of spiking output that underlie behavior. In neocortex, brain state is reflected in the spontaneous activity of the network, which is regulated in part by neuromodulatory input from the brain stem and by local inhibition. We find that fast-spiking, parvalbumin-expressing inhibitory neurons, which exert state-dependent control of network gain and spike patterns, cluster into two stable and functionally distinct subnetworks that are differentially engaged by ascending neuromodulation. One group is excited as a function of increased arousal state; this excitation is driven in part by the increase in cortical norepinephrine that occurs when the locus coeruleus is active. A second group is suppressed during movement when acetylcholine is released into the cortex via projections from the nucleus basalis. These data establish the presence of functionally independent subnetworks of Parvalbumin (PV) cells in the upper layers of the neocortex that are differentially engaged by the ascending reticular activating system

Theta Motion Processing in Fruit Flies

The tiny brains of insects presumably impose significant computational limitations on algorithms controlling their behavior. Nevertheless, they perform fast and sophisticated visual maneuvers. This includes tracking features composed of second-order motion, in which the feature is defined by higher-order image statistics, but not simple correlations in luminance. Flies can track the true direction of even theta motions, in which the first-order (luminance) motion is directed opposite the second-order moving feature. We exploited this paradoxical feature tracking response to dissect the particular image properties that flies use to track moving objects. We find that theta motion detection is not simply a result of steering toward any spatially restricted flicker. Rather, our results show that fly high-order feature tracking responses can be broken down into positional and velocity components – in other words, the responses can be modeled as a superposition of two independent steering efforts. We isolate these elements to show that each has differing influence on phase and amplitude of steering responses, and together they explain the time course of second-order motion tracking responses during flight. These observations are relevant to natural scenes, where moving features can be much more complex

An inhibitory pull-push circuit in frontal cortex.

Push-pull is a canonical computation of excitatory cortical circuits. By contrast, we identify a pull-push inhibitory circuit in frontal cortex that originates in vasoactive intestinal polypeptide (VIP)-expressing interneurons. During arousal, VIP cells rapidly and directly inhibit pyramidal neurons; VIP cells also indirectly excite these pyramidal neurons via parallel disinhibition. Thus, arousal exerts a feedback pull-push influence on excitatory neurons-an inversion of the canonical push-pull of feedforward input

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience

On the Origin of the Functional Architecture of the Cortex

The basic structure of receptive fields and functional maps in primary visual cortex is established without exposure to normal sensory experience and before the onset of the critical period. How the brain wires these circuits in the early stages of development remains unknown. Possible explanations include activity-dependent mechanisms driven by spontaneous activity in the retina and thalamus, and molecular guidance orchestrating thalamo-cortical connections on a fine spatial scale. Here I propose an alternative hypothesis: the blueprint for receptive fields, feature maps, and their inter-relationships may reside in the layout of the retinal ganglion cell mosaics along with a simple statistical connectivity scheme dictating the wiring between thalamus and cortex. The model is shown to account for a number of experimental findings, including the relationship between retinotopy, orientation maps, spatial frequency maps and cytochrome oxidase patches. The theory's simplicity, explanatory and predictive power makes it a serious candidate for the origin of the functional architecture of primary visual cortex

On the origin of the functional architecture of the cortex.

The basic structure of receptive fields and functional maps in primary visual cortex is established without exposure to normal sensory experience and before the onset of the critical period. How the brain wires these circuits in the early stages of development remains unknown. Possible explanations include activity-dependent mechanisms driven by spontaneous activity in the retina and thalamus, and molecular guidance orchestrating thalamo-cortical connections on a fine spatial scale. Here I propose an alternative hypothesis: the blueprint for receptive fields, feature maps, and their inter-relationships may reside in the layout of the retinal ganglion cell mosaics along with a simple statistical connectivity scheme dictating the wiring between thalamus and cortex. The model is shown to account for a number of experimental findings, including the relationship between retinotopy, orientation maps, spatial frequency maps and cytochrome oxidase patches. The theory's simplicity, explanatory and predictive power makes it a serious candidate for the origin of the functional architecture of primary visual cortex

Sparse thalamocortical convergence

How many thalamic neurons converge onto a cortical cell? This is an important question, because the organization of thalamocortical projections can influence the cortical architecture.1,2 Here, we estimate the degree of thalamocortical convergence in primary visual cortex by taking advantage of the cortical expansion-neurons within a restricted volume in primary visual cortex have overlapping receptive fields driven by a smaller set of inputs from the lateral geniculate nucleus.3-5 Under these conditions, the measurements of cortical receptive fields in a population can be used to infer the receptive fields of their geniculate inputs and the weights of their projections using non-negative matrix factorization.6 The analysis reveals sparse connectivity,7 where a handful (~2-6) of thalamic inputs account for 90% of the total synaptic weight to a cortical neuron. Together with previous findings,8 these results paint a picture consistent with the idea that convergence of a few inputs partly determine the retinotopy and tuning properties of cortical cells.8-13