Stability and learning in excitatory synapses by nonlinear inhibitory plasticity

PLoS Computational Biology, Год журнала: 2022, Номер 18(12), С. e1010682 - e1010682

Опубликована: Дек. 2, 2022

Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading either unlimited growth strengths or silencing neuronal activity without additional homeostatic mechanisms. To control strengths, we propose a novel form at inhibitory synapses. Using computational modeling, suggest two key features plasticity, dominance inhibition over excitation nonlinear dependence firing rate postsynaptic neurons whereby change with same sign (potentiate depress) as strengths. We demonstrate that stable realized by this model affects excitatory/inhibitory weight ratios agreement experimental results. Applying disinhibitory signal can gate lead generation receptive fields strong bidirectional connectivity recurrent network. Hence, simultaneously stabilize enable upon disinhibition.

Язык: Английский

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Concurrent Encoding of Sequence Predictability and Event-Evoked Prediction Error in Unfolding Auditory Patterns

Journal of Neuroscience, Год журнала: 2024, Номер 44(14), С. e1894232024 - e1894232024

Опубликована: Фев. 13, 2024

Human listeners possess an innate capacity to discern patterns within rapidly unfolding sensory input. Core questions, guiding ongoing research, focus on the mechanisms through which these representations are acquired and whether brain prioritizes or suppresses predictable signals. Previous work, using fast auditory sequences (tone-pips presented at a rate of 20 Hz), revealed sustained response effects that appear track dynamic predictability sequence. Here, we extend investigation slower (4 permitting isolation responses individual tones. Stimuli were 50 ms tone-pips, ordered into random (RND) regular (REG; repeating pattern 10 frequencies) sequences; Two timing profiles created: in “fast” sequences, tone-pips direct succession (20 Hz); “slow” separated by 200 silent gap Hz). Naive participants ( N = 22; both sexes) passively listened while recorded magnetoencephalography (MEG). Results unveiled heightened magnitude REG when compared RND patterns. This manifested from three tones after onset repetition, even context characterized extended durations (2,500 ms). observation underscores remarkable implicit sensitivity acoustic regularities. Importantly, evoked single exhibited opposite pattern—stronger than sequences. The demonstration simultaneous but opposing reveals concurrent processes shape representation

Язык: Английский

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Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions

Frontiers in Computational Neuroscience, Год журнала: 2022, Номер 16

Опубликована: Июль 4, 2022

While it is universally accepted that the brain makes predictions, there little agreement about how this accomplished and under which conditions. Accurate prediction requires neural circuits to learn store spatiotemporal patterns observed in natural environment, but not obvious such information should be stored, or encoded. Information theory provides a mathematical formalism can used measure efficiency utility of different coding schemes for data transfer storage. This shows codes become efficient when they remove predictable, redundant spatial temporal information. Efficient has been understand retinal computations may also relevant understanding more complicated processing visual cortex. However, literature on cortex varied confusing since same terms are mean things experimental theoretical contexts. In work, we attempt provide clear summary relationship between prediction, review evidence principles explain retina. We then apply framework occurring early visuocortical areas, arguing from rodents largely consistent with predictions model. Finally, respond criticisms suggest ways might design future experiments, particular focus extent make representations environmental statistics.

Язык: Английский

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Novelty detection in an auditory oddball task on freely moving rats

Communications Biology, Год журнала: 2023, Номер 6(1)

Опубликована: Окт. 19, 2023

The relative importance or saliency of sensory inputs depend on the animal's environmental context and behavioural responses to these same can vary over time. Here we show how freely moving rats, trained discriminate between deviant tones embedded in a regular pattern repeating stimuli different variations classic oddball paradigm, detect tones, this discriminability resembles properties that are typical neuronal adaptation described previous studies. Moreover, auditory brainstem response (ABR) latency decreases after training, finding consistent with notion animals develop type plasticity stimuli. Our study suggests existence form long-term memory may modulate level according its relevance, sets ground for future experiments will help disentangle functional mechanisms govern habituation relation adaptation.

Язык: Английский

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Inhibitory plasticity supports replay generalization in the hippocampus

Nature Neuroscience, Год журнала: 2024, Номер 27(10), С. 1987 - 1998

Опубликована: Сен. 3, 2024

Язык: Английский

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Geometry and dynamics of representations in a precisely balanced memory network related to olfactory cortex

eLife, Год журнала: 2025, Номер 13

Опубликована: Янв. 13, 2025

Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these contain both excitatory and inhibitory neurons (E/I assemblies), resulting co-tuning precise balance excitation inhibition. To understand computational consequences E/I under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp adult zebrafish, precisely balanced recurrent homologous piriform cortex. We found stabilized firing rate distributions compared with global Unlike classical models, did not show discrete attractor dynamics. Rather, responses learned inputs were locally constrained onto manifolds ‘focused’ activity into neuronal subspaces. The covariance structure supported pattern classification when was retrieved selected subsets. Networks therefore transformed geometry coding space, continuous representations reflected relatedness an individual’s experience. Such enable fast classification, can support continual learning, may provide basis for higher-order learning cognitive computations.

Язык: Английский

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Hallmarks of Brain Plasticity

Biomedicines, Год журнала: 2025, Номер 13(2), С. 460 - 460

Опубликована: Фев. 13, 2025

Cerebral plasticity is the ability of brain to change and adapt in response experience or learning. Its hallmarks are developmental flexibility, complex interactions between genetic environmental influences, structural-functional changes comprising neurogenesis, axonal sprouting, synaptic remodeling. Studies on have important practical implications. The molecular characteristics may reveal disease course rehabilitative potential patient. Neurological disorders linked with numerous cerebral non-coding RNAs (ncRNAs), particular, microRNAs; discovery their essential role gene regulation was recently recognized awarded a Nobel Prize Physiology Medicine 2024. Herein, we review association its homeostasis ncRNAs, which make them putative targets for RNA-based diagnostics therapeutics. New insight into concept provide additional perspectives functional recovery following damage. Knowledge this phenomenon will enable physicians exploit regulate eloquent networks timely interventions. Future studies pathophysiological mechanisms at macro- microscopic levels advance rehabilitation strategies improve quality life patients neurological diseases.

Язык: Английский

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Computational models of learning and synaptic plasticity

Elsevier eBooks, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks

PLoS Computational Biology, Год журнала: 2025, Номер 21(4), С. e1012910 - e1012910

Опубликована: Апрель 24, 2025

Synaptic plasticity is a key player in the brain’s life-long learning abilities. However, due to experimental limitations, mechanistic link between synaptic rules and network-level computations they enable remain opaque. Here we use evolutionary strategies (ES) meta learn local co-active large recurrent spiking networks with excitatory (E) inhibitory (I) neurons, using parameterizations of increasing complexity. We discover that robustly stabilize network dynamics for all four synapse types acting isolation (E-to-E, E-to-I, I-to-E I-to-I). More complex functions such as familiarity detection can also be included search constraints. our strategy begins fail complexity, it challenging devise loss effectively constrain plausible solutions priori . Moreover, line previous work, find multiple degenerate identical behaviour. As optimization strategy, ES provides one solution at time makes exploration this degeneracy cumbersome. Regardless, glean interdependecies various parameters by considering covariance matrix learned alongside optimal rule ES. Our work proof principle success machine-learning-guided discovery networks, points necessity more elaborate going forward.

Язык: Английский

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Nonlinear transient amplification in recurrent neural networks with short-term plasticity

eLife, Год журнала: 2021, Номер 10

Опубликована: Дек. 13, 2021

To rapidly process information, neural circuits have to amplify specific activity patterns transiently. How the brain performs this nonlinear operation remains elusive. Hebbian assemblies are one possibility whereby strong recurrent excitatory connections boost neuronal activity. However, such amplification is often associated with dynamical slowing of network dynamics, non-transient attractor states, and pathological run-away Feedback inhibition can alleviate these effects but typically linearizes responses reduces gain. Here, we study transient (NTA), a plausible alternative mechanism that reconciles excitation rapid while avoiding above issues. NTA has two distinct temporal phases. Initially, positive feedback selectively amplifies inputs exceed critical threshold. Subsequently, short-term plasticity quenches dynamics into an inhibition-stabilized state. By characterizing in supralinear models, establish resulting onset transients stimulus selective well-suited for speedy information processing. Further, find excitatory-inhibitory co-tuning widens parameter regime which possible absence persistent In summary, provides parsimonious explanation how collaborate networks achieve amplification.

Язык: Английский

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