Knowing what you don’t know: Estimating the uncertainty of feedforward and feedback inputs with prediction-error circuits DOI Creative Commons
Loreen Hertäg, Katharina A. Wilmes, Claudia Clopath

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Дек. 14, 2023

Abstract At any moment, our brains receive a stream of sensory stimuli arising from the world we interact with. Simultaneously, neural circuits are shaped by feedback signals carrying predictions about same inputs experience. Those feedforward and often do not perfectly match. Thus, have challenging task integrating these conflicting streams information according to their reliabilities. However, how keep track both stimulus prediction uncertainty is well understood. Here, propose network model whose core hierarchical prediction-error circuit. We show that can estimate variance using activity negative positive neurons. In line with previous hypotheses, demonstrate rely strongly on if perceived noisy underlying generative process, is, environment stable. Moreover, modulate at onset new stimulus, even this reliable. network, estimation, and, hence, much predictions, be influenced perturbing intricate interplay different inhibitory interneurons. We, therefore, investigate contribution those interneurons weighting inputs. Finally, linked biased perception unravel contribute contraction bias.

Язык: Английский

Opposing Influence of Top-down and Bottom-up Input on Excitatory Layer 2/3 Neurons in Mouse Primary Visual Cortex DOI Creative Commons
Rebecca Jordan, Georg B. Keller

Neuron, Год журнала: 2020, Номер 108(6), С. 1194 - 1206.e5

Опубликована: Окт. 21, 2020

Processing in cortical circuits is driven by combinations of and subcortical inputs. These inputs are often conceptually categorized as bottom-up, conveying sensory information, top-down, contextual information. Using intracellular recordings mouse primary visual cortex, we measured neuronal responses to input, locomotion, visuomotor mismatches. We show that layer 2/3 (L2/3) neurons compute a difference between top-down motor-related input bottom-up flow input. Most L2/3 responded mismatch with either hyperpolarization or depolarization, the size this response was correlated distinct physiological properties. Consistent subtraction had opposing influence on neurons. In infragranular neurons, found no evidence computation were consistent positive integration Our results provide functions bidirectional comparator

Язык: Английский

Процитировано

170

NMDA receptors in visual cortex are necessary for normal visuomotor integration and skill learning DOI Creative Commons
Felix C Widmer, Sean M. O'Toole, Georg B. Keller

и другие.

eLife, Год журнала: 2022, Номер 11

Опубликована: Фев. 16, 2022

The experience of coupling between motor output and visual feedback is necessary for the development visuomotor skills shapes integration in cortex. Whether these experience-dependent changes responses V1 depend on modifications local circuit or are consequence outside remains unclear. Here, we probed role N-methyl-d-aspartate (NMDA) receptor-dependent signaling, which known to be involved neuronal plasticity, mouse primary cortex (V1) during development. We used a knockout NMDA receptors photoactivatable inhibition CaMKII first probe activity as well influence performance task. found that before, but not after, reduced unpredictable stimuli, diminished suppression predictable V1, impaired skill learning later life. Our results demonstrate signaling critical shaping enabling learning.

Язык: Английский

Процитировано

52

Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications DOI Creative Commons
Loreen Hertäg, Claudia Clopath

Proceedings of the National Academy of Sciences, Год журнала: 2022, Номер 119(13)

Опубликована: Март 23, 2022

Significance An influential idea in neuroscience is that neural circuits do not only passively process sensory information but rather actively compare them with predictions thereof. A core element of this comparison prediction-error neurons, the activity which changes upon mismatches between actual and predicted stimuli. While it has been shown these neurons come different variants, largely unresolved how they are simultaneously formed shaped by highly interconnected networks. By using a computational model, we study circuit-level mechanisms give rise to variants neurons. Our results shed light on formation, refinement, robustness circuits, an important step toward better understanding predictive processing.

Язык: Английский

Процитировано

47

The locus coeruleus as a global model failure system DOI Creative Commons
Rebecca Jordan

Trends in Neurosciences, Год журнала: 2023, Номер 47(2), С. 92 - 105

Опубликована: Дек. 14, 2023

Predictive processing models posit that brains constantly attempt to predict their sensory inputs. Prediction errors signal when these predictions are incorrect and thought be instructive signals drive corrective plasticity. Recent findings support the idea locus coeruleus (LC) - a brain-wide neuromodulatory system several types of prediction error. I discuss how proposing LC global model failures: instances where about world strongly violated. Focusing on cortex, explore utility this in learning rate control, circuit may compute signal, view aid our understanding neurodivergence.

Язык: Английский

Процитировано

31

Learning excitatory-inhibitory neuronal assemblies in recurrent networks DOI Creative Commons
Owen Mackwood, Laura Naumann, Henning Sprekeler

и другие.

eLife, Год журнала: 2021, Номер 10

Опубликована: Апрель 26, 2021

Understanding the connectivity observed in brain and how it emerges from local plasticity rules is a grand challenge modern neuroscience. In primary visual cortex (V1) of mice, synapses between excitatory pyramidal neurons inhibitory parvalbumin-expressing (PV) interneurons tend to be stronger for that respond similar stimulus features, although these are not topographically arranged according their preference. The presence such excitatory-inhibitory (E/I) neuronal assemblies indicates stimulus-specific form feedback inhibition. Here, we show activity-dependent synaptic on input output PV generates circuit structure consistent with mouse V1. Computational modeling reveals both forms must act synergy E/I assemblies. Once established, produce competition neurons. Our model suggests can refine circuits actively shape cortical computations.

Язык: Английский

Процитировано

52

Simple synaptic modulations implement diverse novelty computations DOI Creative Commons
Kyle Aitken, Luke Campagnola, Marina Garrett

и другие.

Cell Reports, Год журнала: 2024, Номер 43(5), С. 114188 - 114188

Опубликована: Май 1, 2024

Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of over timescales from seconds to weeks are reflected in the activity excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting multiplicative modulations dependent on presynaptic or pre/postsynaptic activity. With FMSs, network responses that encode emerge under unsupervised continual minimal connectivity constraints. Implementing FMSs within experimentally constrained model visual cortical circuit, demonstrate generalizability by simultaneously fitting absolute, contextual, omission effects. Our also reproduces functional diversity cell subpopulations, leading testable predictions about synaptic dynamics can produce both population-level heterogeneous individual signals. Altogether, our findings simple plasticity mechanisms circuit structure qualitatively distinct complex responses.

Язык: Английский

Процитировано

7

Layer-specific control of inhibition by NDNF interneurons DOI
Laura Naumann, Loreen Hertäg, Jennifer Müller

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(4)

Опубликована: Янв. 22, 2025

Neuronal processing of external sensory input is shaped by internally generated top–down information. In the neocortex, projections primarily target layer 1, which contains NDNF (neuron-derived neurotrophic factor)-expressing interneurons and dendrites pyramidal cells. Here, we investigate hypothesis that shape cortical computations in an unconventional, layer-specific way, exerting presynaptic inhibition on synapses 1 while leaving deeper layers unaffected. We first confirm experimentally auditory cortex, from somatostatin-expressing (SOM) onto neurons are indeed modulated ambient Gamma-aminobutyric acid (GABA). Shifting to a computational model, then show this mechanism introduces distinct mutual motif between synaptic outputs SOM interneurons. This can control way competition for dendritic cells different timescales. thereby information flow redistributing fast slow timescales gating sources inhibition.

Язык: Английский

Процитировано

1

Supralinear dendritic integration in murine dendrite-targeting interneurons DOI Creative Commons
Simonas Griesius, Amy Richardson, Dimitri M. Kullmann

и другие.

eLife, Год журнала: 2025, Номер 13

Опубликована: Янв. 31, 2025

Non-linear summation of synaptic inputs to the dendrites pyramidal neurons has been proposed increase computation capacity through coincidence detection, signal amplification, and additional logic operations such as XOR. Supralinear dendritic integration documented extensively in principal neurons, mediated by several voltage-dependent conductances. It also reported parvalbumin-positive hippocampal basket cells, innervated feedback excitatory synapses. Whether other interneurons, which support feed-forward or inhibition neuron dendrites, exhibit local non-linear excitation is not known. Here, we use patch-clamp electrophysiology, two-photon calcium imaging glutamate uncaging, show that supralinear near-synchronous spatially clustered glutamate-receptor depolarization occurs NDNF-positive neurogliaform cells oriens-lacunosum moleculare interneurons mouse hippocampus. was detected via recordings somatic depolarizations elicited uncaging on fragments, and, concurrent transients. Supralinearity abolished blocking NMDA receptors (NMDARs) but resisted blockade voltage-gated sodium channels. Blocking L-type channels signalling only had a minor effect voltage supralinearity. Dendritic boosting signals argues for previously unappreciated computational complexity dendrite-projecting inhibitory

Язык: Английский

Процитировано

1

Spatial navigation signals in rodent visual cortex DOI Creative Commons
Tom Floßmann, Nathalie L. Rochefort

Current Opinion in Neurobiology, Год журнала: 2020, Номер 67, С. 163 - 173

Опубликована: Дек. 25, 2020

During navigation, animals integrate sensory information with body movements to guide actions. The impact of both navigational and movement-related signals on cortical visual processing remains largely unknown. We review recent studies in awake rodents that have revealed navigation-related the primary cortex (V1) including speed, distance travelled head-orienting movements. Both subcortical inputs convey self-motion related V1 neurons: for example, top-down from secondary motor retrosplenial cortices about head spatial expectations. Within V1, subtypes inhibitory neurons are critical integration signals. conclude potential functional roles gain control, error predictive coding.

Язык: Английский

Процитировано

45

Fast adaptation to rule switching using neuronal surprise DOI Creative Commons
Martin Barry, Wulfram Gerstner

PLoS Computational Biology, Год журнала: 2024, Номер 20(2), С. e1011839 - e1011839

Опубликована: Фев. 20, 2024

In humans and animals, surprise is a physiological reaction to an unexpected event, but how can be linked plausible models of neuronal activity open problem. We propose self-supervised spiking neural network model where signal extracted from increase in after imbalance excitation inhibition. The modulates synaptic plasticity via three-factor learning rule which increases at moments surprise. remains small when transitions between sensory events follow previously learned immediately switching. with several modules, rules are protected against overwriting, as long the number modules larger than total rules—making step towards solving stability-plasticity dilemma neuroscience. Our relates subjective notion specific predictions on circuit level.

Язык: Английский

Процитировано

6