Theory of morphodynamic information processing: Linking sensing to behaviour

Vision Research, Journal Year: 2025, Volume and Issue: 227, P. 108537 - 108537

Published: Jan. 4, 2025

The traditional understanding of brain function has predominantly focused on chemical and electrical processes.However, new research in fruit fly (Drosophila) binocular vision reveals ultrafast photomechanical photoreceptor movements significantly enhance information processing, thereby impacting a fly's perception its environment behaviour.The coding advantages resulting from these mechanical processes suggest that similar physical motion-based strategies may affect neural communication ubiquitously.The theory morphodynamics proposes rapid biomechanical microstructural changes at the level neurons synapses speed efficiency sensory intrinsic thoughts, actions by regulating phasic manner.We propose morphodynamic processing evolved to drive predictive coding, synchronising cognitive across networks match behavioural demands hand effectively.

Language: Английский

---

Ex vivo cortical circuits learn to predict and spontaneously replay temporal patterns

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 4, 2025

Abstract It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, neural mechanisms in place to allow circuits autonomously learn the temporal structure external stimuli generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two patterns using dual-optical stimulation. After 24-h training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay learned during spontaneous activity. Furthermore, some neurons exhibited errors as by larger responses when expected stimulus omitted compared it present. Mechanistically our results indicate learning relied part asymmetric connectivity between distinct neuronal ensembles temporally-ordered activation. These findings further suggest local microcircuits intrinsically capable information generating predictions, rules underlying can be intrinsic not necessarily dependent top-down interactions.

Language: Английский

---

The predictive nature of spontaneous brain activity across scales and species

Neuron, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

---

Inharmonicity enhances brain signals of attentional capture and auditory stream segregation

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

Abstract Harmonicity is an important feature for auditory perception as it influences pitch processing, memory and hearing in noisy environments. However, the neural substrates of processing harmonic inharmonic sounds remain unclear. Here, we systematically manipulated harmonicity synthetic by introducing random jittering to frequencies above fundamental. Using electroencephalography, studied spectral uncertainty induced effect on markers prediction errors—mismatch negativity (MMN) P3a— a roving oddball paradigm. Inharmonic with constant pattern generated similar MMN stronger P3a responses than sounds. In contrast, became undetectable when changed between consecutive sounds, suggesting that errors are weighted sequential but not uncertainty. Interestingly, object-related negativity, response associated segregation objects. Our results suggest inharmonicity induces scene into different streams, captures attention, gives rise specific processes independent from predictive mechanisms underlying deviance detection.

Language: Английский

---

Sensor Movement Drives Emergent Attention and Scalability in Active Neural Cellular Automata

Published: Jan. 1, 2025

Language: Английский

---

Emergent Aspects of the Integration of Sensory and Motor Functions

Brain Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 162 - 162

Published: Feb. 7, 2025

This article delves into the intricate mechanisms underlying sensory integration in executive control of movement, encompassing ideomotor activity, predictive capabilities, and motor systems. It examines interplay between functions, highlighting role cortical subcortical regions central nervous system enhancing environmental interaction. The acquisition skills, procedural memory, representation actions brain are discussed emphasizing significance mental imagery training function. development this aspect sensorimotor can help to advance our understanding interactions control, mechanisms, consciousness. Bridging theoretical insights with practical applications, it sets stage for future innovations clinical rehabilitation, assistive technology, education. ongoing exploration these domains promises uncover new pathways human capability well-being.

Language: Английский

---

A non-Hebbian code for episodic memory

Science Advances, Journal Year: 2025, Volume and Issue: 11(8)

Published: Feb. 21, 2025

Hebbian plasticity has long dominated neurobiological models of memory formation. Yet, rules operating on one-shot episodic timescales rarely depend both pre- and postsynaptic spiking, challenging theory in this crucial regime. Here, we present an model governed by a simpler rule depending only presynaptic activity. We show that rule, capitalizing high-dimensional neural activity with restricted transitions, naturally stores episodes as paths through complex state spaces like those underlying world model. The resulting traces, which term path vectors, are highly expressive decodable odor-tracking algorithm. vectors robust alternatives to support sequential associative recall, along policy learning, shed light specific hippocampal rules. Thus, non-Hebbian is sufficient for flexible learning well-suited encode policies

Language: Английский

---

The many roles of precision in action

Published: Aug. 2, 2024

Active inference describes (Bayes optimal) behaviour as motivated by the minimisation of surprise one’s sensory observations, through optimisation a generative model hidden causes data in brain. One active inference’s key appeals is its conceptualisation precision biasing neuronal communication and thus within models. The importance perceptual evident—many studies have demonstrated getting estimates right for normal (healthy) sensation perception. Here, we highlight many roles plays action; i.e., processes action that rely on adequate precision—from decision making planning to initiation control muscle movement itself. Thereby, focus recent development hierarchical “mixed” models—generative models spanning multiple levels discrete (categorical) continuous inference. These kinds open up new perspectives unified description computation action. We shall how these reflect action—from execution—and associated pathologies if estimation goes wrong. Thereby also discuss potential biological implementation message passing, focusing role neuromodulatory systems mediating different

Language: Английский

---

Desegregation of neuronal predictive processing

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 7, 2024

Abstract Neural circuits construct internal ‘world-models’ to guide behavior. The predictive processing framework posits that neural activity signaling sensory predictions and concurrently computing prediction-errors is a signature of those models. Here, understand how the brain generates for complex sensorimotor signals, we investigate emergence high-dimensional, multi-modal representations in recurrent networks. We find robust arises network with loose excitatory/inhibitory balance. Contrary previous proposals functionally specialized cell-types, exhibits desegregation stimulus prediction-error representations. confirmed these model by experimentally probing predictive-coding using rich stimulus-set violate learned expectations. When constrained data, our further reveals makes concrete testable experimental distinct functional roles excitatory inhibitory neurons, neurons different layers along laminar hierarchy, predictions. These results together imply natural conditions, models are highly distributed, yet structured allow flexible readout behaviorally-relevant information. generality advances understanding computation across species, incorporating types computations into unified framework.

Language: Английский

---

The Many Roles of Precision in Action

Entropy, Journal Year: 2024, Volume and Issue: 26(9), P. 790 - 790

Published: Sept. 14, 2024

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise one’s sensory observations, through optimisation a generative model (of hidden causes data) in brain. One active inference’s key appeals is its conceptualisation precision biasing neuronal communication and, thus, within models. The importance perceptual evident—many studies have demonstrated ensuring estimates are correct for normal (healthy) sensation and perception. Here, we highlight many roles plays action, i.e., processes that rely on adequate precision, from decision making action planning to initiation control muscle movement itself. Thereby, focus recent development hierarchical, “mixed” models—generative models spanning multiple levels discrete continuous inference. These kinds open up new perspectives unified description hierarchical computation, implementation, action. how these reflect action—from execution—and associated pathologies if estimation goes wrong. We also discuss potential biological implementation message passing, focusing role neuromodulatory systems mediating different precision.

Language: Английский

---