Synaptic Plasticity in Cortical Inhibitory Neurons: What Mechanisms May Help to Balance Synaptic Weight Changes?

Chaotic recurrent neural networks for brain modelling: A review

Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous activity. While the precise function of brain chaotic activity is still puzzling, we know that chaos confers many advantages. From a computational perspective, chaos enhances the complexity of network dynamics. From a behavioural point of view, chaotic activity could generate the variability required for exploration. Furthermore, information storage and transfer are maximized at the critical border between order and chaos. Despite these benefits, many computational brain models avoid incorporating spontaneous chaotic activity due to the challenges it poses for learning algorithms. In recent years, however, multiple approaches have been proposed to overcome this limitation. As a result, many different algorithms have been developed, initially within the reservoir computing paradigm. Over time, the field has evolved to increase the biological plausibility and performance of the algorithms, sometimes going beyond the reservoir computing framework. In this review article, we examine the computational benefits of chaos and the unique properties of chaotic recurrent neural networks, with a particular focus on those typically utilized in reservoir computing. We also provide a detailed analysis of the algorithms designed to train chaotic RNNs, tracing their historical evolution and highlighting key milestones in their development. Finally, we explore the applications and limitations of chaotic RNNs for brain modelling, consider their potential broader impacts beyond neuroscience, and outline promising directions for future research.

A neuronal least-action principle for real-time learning in cortical circuits

One of the most fundamental laws of physics is the principle of least action. Motivated by its predictive power, we introduce a neuronal least-action principle for cortical processing of sensory streams to produce appropriate behavioral outputs in real time. The principle postulates that the voltage dynamics of cortical pyramidal neurons prospectively minimizes the local somato-dendritic mismatch error within individual neurons. For output neurons, the principle implies minimizing an instantaneous behavioral error. For deep network neurons, it implies the prospective firing to overcome integration delays and correct for possible output errors right in time. The neuron-specific errors are extracted in the apical dendrites of pyramidal neurons through a cortical microcircuit that tries to explain away the feedback from the periphery, and correct the trajectory on the fly. Any motor output is in a moving equilibrium with the sensory input and the motor feedback during the ongoing sensory-motor transform. Online synaptic plasticity reduces the somatodendritic mismatch error within each cortical neuron and performs gradient descent on the output cost at any moment in time. The neuronal least-action principle offers an axiomatic framework to derive local neuronal and synaptic laws for global real-time computation and learning in the brain.

Extracellular ATP inhibits excitatory synaptic input on parvalbumin positive interneurons and attenuates gamma oscillations via P2X4 receptors

BACKGROUND AND PURPOSE

P2X4 receptors (P2X4R) are ligand gated cation channels that are activated by extracellular ATP released by neurons and glia. The receptors are widely expressed in the brain and have fractional calcium currents comparable with NMDA receptors. Although P2X4Rs have been reported to modulate synaptic transmission and plasticity, their involvement in shaping neuronal network activity remains to be elucidated.

EXPERIMENTAL APPROACH

We investigated the effects of P2X receptors at network and synaptic level using local field potential electrophysiology, whole cell patch clamp recordings and calcium imaging in fast spiking parvalbumin positive interneurons (PVINs) in rat and mouse hippocampal slices. The stable ATP analogue ATPγS, selective antagonists and P2X4R knockout mice were used.

KEY RESULTS

The P2XR agonist ATPγS reversibly decreased the power of gamma oscillations. This inhibition could be antagonized by the selective P2X4R antagonist PSB-12062 and was not observed in P2X4-/- mice. The phasic excitatory inputs of CA3 PVINs were one of the main regulators of the gamma power. Associational fibre compound excitatory postsynaptic currents (cEPSCs) in CA3 PVINs were inhibited by P2X4R activation. This effect was reversible, dependent on intracellular calcium and dynamin-dependent internalization of AMPA receptors.

CONCLUSIONS AND IMPLICATIONS

The results indicate that P2X4Rs are an important source of dendritic calcium in CA3 PVINs, thereby regulating excitatory synaptic inputs onto the cells and presumably the state of gamma oscillations in the hippocampus. P2X4Rs represent an effective target to modulate hippocampal network activity in pathophysiological conditions such as Alzheimer's disease and schizophrenia.

Disuse-driven plasticity in the human thalamus and putamen

Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.

Wired together, change together: Spike timing modifies transmission in converging assemblies

The precise timing of neuronal spikes may lead to changes in synaptic connectivity and is thought to be crucial for learning and memory. However, the effect of spike timing on neuronal connectivity in the intact brain remains unknown. Using closed-loop optogenetic stimulation in CA1 of freely moving mice, we generated unique spike patterns between presynaptic pyramidal cells (PYRs) and postsynaptic parvalbumin (PV)-immunoreactive cells. The stimulation led to spike transmission changes that occurred together across all presynaptic PYRs connected to the same postsynaptic PV cell. The precise timing of all presynaptic and postsynaptic cell spikes affected transmission changes. These findings reveal an unexpected plasticity mechanism, in which the spike timing of an entire cell assembly has a more substantial impact on effective connectivity than that of individual cell pairs.

Heterosynaptic plasticity-induced modulation of synapses

Plasticity is a common feature of synapses that is stated in different ways and occurs through several mechanisms. The regular action of the brain needs to be balanced in several neuronal and synaptic features, one of which is synaptic plasticity. The different homeostatic processes, including the balance between excitation/inhibition or homeostasis of synaptic weights at the single-neuron level, may obtain this. Homosynaptic Hebbian-type plasticity causes associative alterations of synapses. Both homosynaptic and heterosynaptic plasticity characterize the corresponding aspects of adjustable synapses, and both are essential for the regular action of neural systems and their plastic synapses.In this review, we will compare homo- and heterosynaptic plasticity and the main factors affecting the direction of plastic changes. This review paper will also discuss the diverse functions of the different kinds of heterosynaptic plasticity and their properties. We argue that a complementary system of heterosynaptic plasticity demonstrates an essential cellular constituent for homeostatic modulation of synaptic weights and neuronal activity.

Cognitive-Affective Functions of the Cerebellum

The cerebellum, traditionally associated with motor coordination and balance, also plays a crucial role in various aspects of higher-order function and dysfunction. Emerging research has shed light on the cerebellum's broader contributions to cognitive, emotional, and reward processes. The cerebellum's influence on autonomic function further highlights its significance in regulating motivational and emotional states. Perturbations in cerebellar development and function have been implicated in various neurodevelopmental disorders, including autism spectrum disorder and attention deficit hyperactivity disorder. An increasing appreciation for neuropsychiatric symptoms that arise from cerebellar dysfunction underscores the importance of elucidating the circuit mechanisms that underlie complex interactions between the cerebellum and other brain regions for a comprehensive understanding of complex behavior. By briefly discussing new advances in mapping cerebellar function in affective, cognitive, autonomic, and social processing and reviewing the role of the cerebellum in neuropathology beyond the motor domain, this Mini-Symposium review aims to provide a broad perspective of cerebellar intersections with the limbic brain in health and disease.

Learning from inhibition: Functional roles of hippocampal CA1 inhibition in spatial learning and memory

Hippocampal inhibitory interneurons exert a powerful influence on learning and memory. Inhibitory interneurons are known to play a major role in many diseases that affect memory, and to strongly influence brain functions required for memory-related tasks. While previous studies involving genetic, optogenetic, and pharmacological manipulations have shown that hippocampal interneurons play essential roles in spatial and episodic learning and memory, exactly how interneurons affect local circuit computations during spatial navigation is not well understood. Given the significant anatomical, morphological, and functional heterogeneity in hippocampal interneurons, one may suspect cell-type specific roles in circuit computations. Here, we review emerging evidence of CA1 hippocampal interneurons' role in local circuit computations that support spatial learning and memory and discuss open questions about CA1 interneurons in spatial learning.

Translational neuronal ensembles: Neuronal microcircuits in psychology, physiology, pharmacology and pathology

Multi-recording techniques show evidence that neurons coordinate their firing forming ensembles and that brain networks are made by connections between ensembles. While “canonical” microcircuits are composed of interconnected principal neurons and interneurons, it is not clear how they participate in recorded neuronal ensembles: “groups of neurons that show spatiotemporal co-activation”. Understanding synapses and their plasticity has become complex, making hard to consider all details to fill the gap between cellular-synaptic and circuit levels. Therefore, two assumptions became necessary: First, whatever the nature of the synapses these may be simplified by “functional connections”. Second, whatever the mechanisms to achieve synaptic potentiation or depression, the resultant synaptic weights are relatively stable. Both assumptions have experimental basis cited in this review, and tools to analyze neuronal populations are being developed based on them. Microcircuitry processing followed with multi-recording techniques show temporal sequences of neuronal ensembles resembling computational routines. These sequences can be aligned with the steps of behavioral tasks and behavior can be modified upon their manipulation, supporting the hypothesis that they are memory traces. In vitro, recordings show that these temporal sequences can be contained in isolated tissue of histological scale. Sequences found in control conditions differ from those recorded in pathological tissue obtained from animal disease models and those recorded after the actions of clinically useful drugs to treat disease states, setting the basis for new bioassays to test drugs with potential clinical use. These findings make the neuronal ensembles theoretical framework a dynamic neuroscience paradigm.

A synaptic signal for novelty processing in the hippocampus

Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Memory formation and recall are complementary processes within the hippocampus. Here the authors demonstrate a synaptic signal of novelty in the hippocampus and provide a computational framework for how such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Enhanced Non-Associative Long-Term Potentiation in Immature Granule Cells in the Dentate Gyrus of Adult Rats

The dentate gyrus is one of the few sites of neurogenesis in the adult brain. Integration of new-generated granule cells into the hippocampal circuitry provides a substrate for structural plasticity, fundamental for normal function of adult hippocampus. However, mechanisms of synaptic plasticity that mediate integration of new-generated granule cells into the existing circuitry remain poorly understood. Especially mechanisms of plasticity at GABA-ergic synapses remain elusive. Here, we show that postsynaptic spiking without presynaptic activation can induce heterosynaptic, non-associative plasticity at GABA-ergic inputs to both immature and mature granule cells. In both immature and mature neurons, plastic changes were bidirectional and individual inputs could express long-term potentiation (LTP) or long-term depression (LTD), or do not change. However, properties of non-associative plasticity dramatically change with maturation of newly generated granule cells: while in immature cells there was a clear predominance of non-associative LTP and net potentiation across the inputs, in mature neurons, potentiation and depression were balanced with no net change on average. We conclude that GABA-ergic inputs to granule cells are plastic, and that the rules for induction of non-associative plasticity change with maturation. We propose that potentiation-biased non-associative plasticity of GABA-ergic transmission might help to counter-balance an increase of excitatory drive that is facilitated by enhanced LTP at glutamatergic synapses in maturating granule cells. Such mechanism might help to build a strong GABA-ergic input to surviving active new cells, necessary for normal function of mature granule cells, which operate under a tight inhibitory control and generate sparse spiking activity.

Heterogeneous Responses to Changes in Inhibitory Synaptic Strength in Networks of Spiking Neurons

How does the dynamics of neurons in a network respond to changes in synaptic weights? Answer to this question would be important for a full understanding of synaptic plasticity. In this article, we report our numerical study of the effects of changes in inhibitory synaptic weights on the spontaneous activity of networks of spiking neurons with conductance-based synapses. Networks with biologically realistic features, which were reconstructed from multi-electrode array recordings taken in a cortical neuronal culture, and their modifications were used in the simulations. The magnitudes of the synaptic weights of all the inhibitory connections are decreased by a uniform amount subjecting to the condition that inhibitory connections would not be turned into excitatory ones. Our simulation results reveal that the responses of the neurons are heterogeneous: while the firing rate of some neurons increases as expected, the firing rate of other neurons decreases or remains unchanged. The same results show that heterogeneous responses also occur for an enhancement of inhibition. This heterogeneity in the responses of neurons to changes in inhibitory synaptic strength suggests that activity-induced modification of synaptic strength does not necessarily generate a positive feedback loop on the dynamics of neurons connected in a network. Our results could be used to understand the effects of bicuculline on spiking and bursting activities of neuronal cultures. Using reconstructed networks with biologically realistic features enables us to identify a long-tailed distribution of average synaptic weights for outgoing links as a crucial feature in giving rise to bursting in neuronal networks and in determining the overall response of the whole network to changes in synaptic strength. For networks whose average synaptic weights for outgoing links have a long-tailed distribution, bursting is observed and the average firing rate of the whole network increases upon inhibition suppression or decreases upon inhibition enhancement. For networks whose average synaptic weights for outgoing links are approximately normally distributed, bursting is not found and the average firing rate of the whole network remains approximately constant upon changes in inhibitory synaptic strength.

Hippocampal SIRT1-Mediated Synaptic Plasticity and Glutamatergic Neuronal Excitability Are Involved in Prolonged Cognitive Dysfunction of Neonatal Rats Exposed to Propofol

Neonates who receive repeated or prolonged general anesthesia before the age of 4 are at a significantly higher risk of developing cognitive dysfunction later in life. In this study, we investigated the effects of repeated neonatal propofol exposure on hippocampal synaptic plasticity, neuronal excitability, and cognitive function. Adeno-associated SIRT1 virus with CaMKIIɑ promotor and a viral vector carrying the photosensitive gene ChR2 with the CaMKIIɑ promotor, as well as their control vectors, were stereotaxically injected into the hippocampal CA1 region of postnatal day 5 (PND-5) rats. PND-7 rats were given intraperitoneal injection of 60 mg/kg propofol or fat emulsion for three consecutive days. Western blotting, Golgi staining, and double immunofluorescence staining were used to evaluate the SIRT1 expression, synaptic plasticity, and the excitability of neurons in the hippocampal CA1 region. The Morris water maze (MWM) test was conducted on PND-30 to assess the learning and memory abilities of rats. Repeated neonatal propofol exposure reduced SIRT1 expression, suppressed synaptic plasticity, decreased glutamatergic neuron excitability in the hippocampus, and damaged learning and memory abilities. Overexpression of SIRT1 attenuated propofol-induced cognitive dysfunction, excitation-inhibition imbalance, and synaptic plasticity damage. After optogenetic stimulation of glutamatergic neurons in the hippocampal CA1 region, the learning and memory abilities of rats exposed to propofol were improved on PND-30. Our findings demonstrate that SIRT1 plays an important role in cognitive dysfunction induced by repeated neonatal propofol exposure by suppressing synaptic plasticity and neuronal excitability.

A stable proportion of Purkinje cell inputs from parallel fibers are silent during cerebellar maturation

Cerebellar Purkinje neurons integrate information transmitted at excitatory synapses formed by granule cells. Although these synapses are considered essential sites for learning, most of them appear not to transmit any detectable electrical information and have been defined as silent. It has been proposed that silent synapses are required to maximize information storage capacity and ensure its reliability, and hence to optimize cerebellar operation. Such optimization is expected to occur once the cerebellar circuitry is in place, during its maturation and the natural and steady improvement of animal agility. We therefore investigated whether the proportion of silent synapses varies over this period, from the third to the sixth postnatal week in mice. Selective expression of a calcium indicator in granule cells enabled quantitative mapping of presynaptic activity, while postsynaptic responses were recorded by patch clamp in acute slices. Through this approach and the assessment of two anatomical features (the distance that separates adjacent planar Purkinje dendritic trees and the synapse density), we determined the average excitatory postsynaptic potential per synapse. Its value was four to eight times smaller than responses from paired recorded detectable connections, consistent with over 70% of synapses being silent. These figures remained remarkably stable across maturation stages. According to the proposed role for silent synapses, our results suggest that information storage capacity and reliability are optimized early during cerebellar maturation. Alternatively, silent synapses may have roles other than adjusting the information storage capacity and reliability.

Altered Heterosynaptic Plasticity Impairs Visual Discrimination Learning in Adenosine A1 Receptor Knock-Out Mice

Theoretical and modeling studies demonstrate that heterosynaptic plasticity-changes at synapses inactive during induction-facilitates fine-grained discriminative learning in Hebbian-type systems, and helps to achieve a robust ability for repetitive learning. A dearth of tools for selective manipulation has hindered experimental analysis of the proposed role of heterosynaptic plasticity in behavior. Here we circumvent this obstacle by testing specific predictions about the behavioral consequences of the impairment of heterosynaptic plasticity by experimental manipulations to adenosine A1 receptors (A1Rs). Our prior work demonstrated that the blockade of adenosine A1 receptors impairs heterosynaptic plasticity in brain slices and, when implemented in computer models, selectively impairs repetitive learning on sequential tasks. Based on this work, we predict that A1R knock-out (KO) mice will express (1) impairment of heterosynaptic plasticity and (2) behavioral deficits in learning on sequential tasks. Using electrophysiological experiments in slices and behavioral testing of animals of both sexes, we show that, compared with wild-type controls, A1R KO mice have impaired synaptic plasticity in visual cortex neurons, coupled with significant deficits in visual discrimination learning. Deficits in A1R knockouts were seen specifically during relearning, becoming progressively more apparent with learning on sequential visual discrimination tasks of increasing complexity. These behavioral results confirm our model predictions and provide the first experimental evidence for a proposed role of heterosynaptic plasticity in organism-level learning. Moreover, these results identify heterosynaptic plasticity as a new potential target for interventions that may help to enhance new learning on a background of existing memories.SIGNIFICANCE STATEMENT Understanding how interacting forms of synaptic plasticity mediate learning is fundamental for neuroscience. Theory and modeling revealed that, in addition to Hebbian-type associative plasticity, heterosynaptic changes at synapses that were not active during induction are necessary for stable system operation and fine-grained discrimination learning. However, lacking tools for selective manipulation prevented behavioral analysis of heterosynaptic plasticity. Here we circumvent this barrier: from our prior experimental and computational work we predict differential behavioral consequences of the impairment of Hebbian-type versus heterosynaptic plasticity. We show that, in adenosine A1 receptor knock-out mice, impaired synaptic plasticity in visual cortex neurons is coupled with specific deficits in learning sequential, increasingly complex visual discrimination tasks. This provides the first evidence linking heterosynaptic plasticity to organism-level learning.