Global enhancement of cortical excitability following coactivation of large neuronal populations

Learning in a sensory cortical microstimulation task is associated with elevated representational stability

Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.

Microstimulation of sensory cortex engages natural sensory representations

Cortical activity patterns occupy a small subset of possible network states. If this is due to intrinsic network properties, microstimulation of sensory cortex should evoke activity patterns resembling those observed during natural sensory input. Here, we use optical microstimulation of virally transfected layer 2/3 pyramidal neurons in the mouse primary vibrissal somatosensory cortex to compare artificially evoked activity with natural activity evoked by whisker touch and movement ("whisking"). We find that photostimulation engages touch- but not whisking-responsive neurons more than expected by chance. Neurons that respond to photostimulation and touch or to touch alone exhibit higher spontaneous pairwise correlations than purely photoresponsive neurons. Exposure to several days of simultaneous touch and optogenetic stimulation raises both overlap and spontaneous activity correlations among touch and photoresponsive neurons. We thus find that cortical microstimulation engages existing cortical representations and that repeated co-presentation of natural and artificial stimulation enhances this effect.

Frequency modulation of cortical rhythmicity governs behavioral variability, excitability and synchrony of neurons in the visual cortex

Research in cognitive neuroscience has renewed the idea that brain oscillations are a core organization implicated in fundamental brain functions. Growing evidence reveals that the characteristic features of these oscillations, including power, phase and frequency, are highly non-stationary, fluctuating alongside alternations in sensation, cognition and behavior. However, there is little consensus on the functional implications of the instantaneous frequency variation in cortical excitability and concomitant behavior. Here, we capitalized on intracortical electrophysiology in the macaque monkey's visual area MT performing a visuospatial discrimination task with visual cues. We observed that the instantaneous frequency of the theta-alpha oscillations (4-13 Hz) is modulated among specific neurons whose RFs overlap with the cued stimulus location. Interestingly, we found that such frequency modulation is causally correlated with MT excitability at both scales of individual and ensemble of neurons. Moreover, studying the functional relevance of frequency variations indicated that the average theta-alpha frequencies foreshadow the monkey's reaction time. Our results also revealed that the neural synchronization strength alters with the average frequency shift in theta-alpha oscillations, suggesting frequency modulation is critical for mutually adjusting MTs' rhythms. Overall, our findings propose that theta-alpha frequency variations modulate MT's excitability, regulate mutual neurons' rhythmicity and indicate variability in behavior.

Altered pain sensitivity in 5×familial Alzheimer disease mice is associated with dendritic spine loss in anterior cingulate cortex pyramidal neurons

ABSTRACT

Chronic pain is highly prevalent. Individuals with cognitive disorders such as Alzheimer disease are a susceptible population in which pain is frequently difficult to diagnosis. It is still unclear whether the pathological changes in patients with Alzheimer disease will affect pain processing. Here, we leverage animal behavior, neural activity recording, optogenetics, chemogenetics, and Alzheimer disease modeling to examine the contribution of the anterior cingulate cortex (ACC) neurons to pain response. The 5× familial Alzheimer disease mice show alleviated mechanical allodynia which can be regained by the genetic activation of ACC excitatory neurons. Furthermore, the lower peak neuronal excitation, delayed response initiation, as well as the dendritic spine reduction of ACC pyramidal neurons in 5×familial Alzheimer disease mice can be mimicked by Rac1 or actin polymerization inhibitor in wild-type (WT) mice. These findings indicate that abnormal of pain sensitivity in Alzheimer disease modeling mice is closely related to the variation of neuronal activity and dendritic spine loss in ACC pyramidal neurons, suggesting the crucial role of dendritic spine density in pain processing.

Formation and computational implications of assemblies in neural circuits

In the brain, patterns of neural activity represent sensory information and store it in non-random synaptic connectivity. A prominent theoretical hypothesis states that assemblies, groups of neurons that are strongly connected to each other, are the key computational units underlying perception and memory formation. Compatible with these hypothesised assemblies, experiments have revealed groups of neurons that display synchronous activity, either spontaneously or upon stimulus presentation, and exhibit behavioural relevance. While it remains unclear how assemblies form in the brain, theoretical work has vastly contributed to the understanding of various interacting mechanisms in this process. Here, we review the recent theoretical literature on assembly formation by categorising the involved mechanisms into four components: synaptic plasticity, symmetry breaking, competition and stability. We highlight different approaches and assumptions behind assembly formation and discuss recent ideas of assemblies as the key computational unit in the brain. Abstract figure legend Assembly Formation. Assemblies are groups of strongly connected neurons formed by the interaction of multiple mechanisms and with vast computational implications. Four interacting components are thought to drive assembly formation: synaptic plasticity, symmetry breaking, competition and stability. This article is protected by copyright. All rights reserved.

Excitatory-inhibitory balance modulates the formation and dynamics of neuronal assemblies in cortical networks

Repetitive activation of subpopulations of neurons leads to the formation of neuronal assemblies, which can guide learning and behavior. Recent technological advances have made the artificial induction of these assemblies feasible, yet how various parameters of induction can be optimized is not clear. Here, we studied this question in large-scale cortical network models with excitatory-inhibitory balance. We found that the background network in which assemblies are embedded can strongly modulate their dynamics and formation. Networks with dominant excitatory interactions enabled a fast formation of assemblies, but this was accompanied by recruitment of other non-perturbed neurons, leading to some degree of nonspecific induction. On the other hand, networks with strong excitatory-inhibitory interactions ensured that the formation of assemblies remained constrained to the perturbed neurons, but slowed down the induction. Our results suggest that these two regimes can be suitable for computational and cognitive tasks with different trade-offs between speed and specificity.

Molecular Tools for Targeted Control of Nerve Cell Electrical Activity. Part II

In modern life sciences, the issue of a specific, exogenously directed manipulation of a cell's biochemistry is a highly topical one. In the case of electrically excitable cells, the aim of the manipulation is to control the cells' electrical activity, with the result being either excitation with subsequent generation of an action potential or inhibition and suppression of the excitatory currents. The techniques of electrical activity stimulation are of particular significance in tackling the most challenging basic problem: figuring out how the nervous system of higher multicellular organisms functions. At this juncture, when neuroscience is gradually abandoning the reductionist approach in favor of the direct investigation of complex neuronal systems, minimally invasive methods for brain tissue stimulation are becoming the basic element in the toolbox of those involved in the field. In this review, we describe three approaches that are based on the delivery of exogenous, genetically encoded molecules sensitive to external stimuli into the nervous tissue. These approaches include optogenetics (overviewed in Part I), as well as chemogenetics and thermogenetics (described here, in Part II), which is significantly different not only in the nature of the stimuli and structure of the appropriate effector proteins, but also in the details of experimental applications. The latter circumstance is an indication that these are rather complementary than competing techniques.