Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network DOI
Yibo Chen, Jonathan Chien, Bing Dai

et al.

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(3), P. 036051 - 036051

Published: June 1, 2024

Abstract Objective. Distributed hypothalamic-midbrain neural circuits help orchestrate complex behavioral responses during social interactions. Given rapid advances in optical imaging, it is a fundamental question how population-averaged activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with behaviors question. This paper aims to investigate the correspondence between MFP data and behaviors. Approach: We propose state-space analysis framework characterize mouse based on dynamic latent variable models, which include continuous-state linear dynamical system discrete-state hidden semi-Markov model. validate these models extensive recordings aggressive mating male-male male-female interactions, respectively. Main results: Our results show that are capable of capturing both temporal structure associated states, produce interpretable states. approach also validated computer simulations presence known ground truth. Significance: Overall, approaches provide examine dynamics underlying reveals mechanistic insights into relevant networks.

Language: Английский

Cell-type-specific population dynamics of diverse reward computations DOI Creative Commons
Emily L. Sylwestrak, YoungJu Jo,

Sam Vesuna

et al.

Cell, Journal Year: 2022, Volume and Issue: 185(19), P. 3568 - 3587.e27

Published: Sept. 1, 2022

Computational analysis of cellular activity has developed largely independently modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, computational features), we identified encoding reward-predictive cues reward outcomes in distinct genetically defined neural populations, including TH+ cells Tac1+ cells. Data from targeted recordings were used train an optimized nonlinear dynamical systems model revealed dynamics consistent a line attractor. High-density, cell-type-specific electrophysiological optogenetic perturbation provided supporting evidence model. Reverse-engineering predicted how might integrate history, which was complemented by vivo experimentation. This integrated describes process data-driven models population can generate frame actionable hypotheses investigation biological systems.

Language: Английский

Citations

48
Development of an Integrated System of sEMG Signal Acquisition, Processing, and Analysis with AI Techniques DOI Creative Commons
Filippo Laganá, Danilo Pratticò, Giovanni Angiulli

et al.

Signals, Journal Year: 2024, Volume and Issue: 5(3), P. 476 - 493

Published: July 26, 2024

The development of robust circuit structures remains a pivotal milestone in electronic device research. This article proposes an integrated hardware–software system designed for the acquisition, processing, and analysis surface electromyographic (sEMG) signals. analyzes sEMG signals to understand muscle function neuromuscular control, employing convolutional neural networks (CNNs) pattern recognition. electrical analyzed on healthy unhealthy subjects are acquired using meticulously developed featuring biopotential acquisition electrodes. captured database extracted, classified, interpreted by application CNNs with aim identifying patterns indicative problems. By leveraging advanced learning techniques, proposed method addresses non-stationary nature recordings mitigates cross-talk effects commonly observed interference sensors. integration AI algorithm signal enhances qualitative outcomes eliminating redundant information. reveals their effectiveness accurately deciphering complex data from signals, problems high precision. paper contributes landscape biomedical research, advocating computational techniques unravel physiological phenomena enhance utility analysis.

Language: Английский

Citations

14
A tonically active master neuron modulates mutually exclusive motor states at two timescales DOI Creative Commons
Jun Meng, Tosif Ahamed, Bin Yu

et al.

Science Advances, Journal Year: 2024, Volume and Issue: 10(15)

Published: April 10, 2024

Continuity of behaviors requires animals to make smooth transitions between mutually exclusive behavioral states. Neural principles that govern these are not well understood. Caenorhabditis elegans spontaneously switch two opposite motor states, forward and backward movement, a phenomenon thought reflect the reciprocal inhibition interneurons AVB AVA. Here, we report spontaneous locomotion their corresponding circuits separately controlled. AVA neither functionally equivalent nor strictly reciprocally inhibitory. AVA, but AVB, maintains depolarized membrane potential. While phasically inhibits promoting interneuron at fast timescale, it tonic, extrasynaptic excitation on over longer timescale. We propose with tonic phasic activity polarities different timescales, acts as master neuron break symmetry underlying circuits. This model offers parsimonious solution for sustained consisted

Language: Английский

Citations

11
Hierarchical behavior control by a single class of interneurons DOI Creative Commons
Jing Huo, Tianqi Xu, Qi Liu

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(47)

Published: Nov. 12, 2024

Animal behavior is organized into nested temporal patterns that span multiple timescales. This hierarchy believed to arise from a hierarchical neural architecture: Neurons near the top of are involved in planning, selecting, initiating, and maintaining motor programs, whereas those bottom act concert produce fine spatiotemporal activity. In Caenorhabditis elegans , on long timescale emerges ordered flexible transitions between different behavioral states, such as forward, reversal, turn. On short timescale, parts animal body coordinate fast rhythmic bending sequences directional movements. Here, we show Sublateral Anterior A (SAA), class interneurons enable cross-communication dorsal ventral head neurons, play dual role shaping dynamics SAA regulate stabilize activity during forward same neurons suppress spontaneous reversals facilitate reversal termination by inhibiting Ring Interneuron M (RIM), an integrating neuron helps maintain state. These results suggest feedback lower-level cell assembly higher-level command center essential for bridging at levels.

Language: Английский

Citations

5
Long sequence Hopfield memory* DOI

Hamza Tahir Chaudhry,

Jacob A. Zavatone-Veth, Dmitry Krotov

et al.

Journal of Statistical Mechanics Theory and Experiment, Journal Year: 2024, Volume and Issue: 2024(10), P. 104024 - 104024

Published: Oct. 21, 2024

Abstract Sequence memory is an essential attribute of natural and artificial intelligence that enables agents to encode, store, retrieve complex sequences stimuli actions. Computational models sequence have been proposed where recurrent Hopfield-like neural networks are trained with temporally asymmetric Hebbian rules. However, these suffer from limited capacity (maximal length the stored sequence) due interference between memories. Inspired by recent work on Dense Associative Memories, we expand introducing a nonlinear interaction term, enhancing separation patterns. We derive novel scaling laws for respect network size, significantly outperforming existing based traditional Hopfield networks, verify theoretical results numerical simulation. Moreover, introduce generalized pseudoinverse rule recall highly correlated Finally, extend this model store variable timing states’ transitions describe biologically-plausible implementation, connections motor neuroscience.

Language: Английский

Citations

4
THE PROMISE OF INVESTIGATING NEURAL VARIABILITY IN PSYCHIATRIC DISORDERS DOI Creative Commons

Konstantinos Tsikonofilos,

Arvind Kumar, Konstantinos Ampatzis

et al.

Biological Psychiatry, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Olfactory bulb tracks breathing rhythms and place in freely behaving mice DOI Open Access
Scott C. Sterrett, Teresa M Findley,

Sidney E Rafilson

et al.

Published: March 11, 2025

Vertebrates sniff to control the odor samples that enter their nose. These can not only help identify odorous objects, but also locations and events. However, there is no receptor for place or time. Therefore, take full advantage of olfactory information, an animal’s brain must contextualize odor-driven activity with information about when, where, how they sniffed. To better understand contextual in system, we captured breathing movements mice while recording from bulb. In stimulus- task-free experiments, structure into persistent rhythmic states which are synchronous statelike ongoing neuronal population activity. reflect a strong dependence individual neuron on variation frequency, display using “sniff fields” quantify generalized linear models. addition, many bulb neurons have “place significant firing allocentric location, were comparable hippocampal recorded under same conditions. At level, mouse’s location be decoded similar accuracy hippocampus. Olfactory sensitivity cannot explained by rhythms scent marks. Taken together, show mouse tracks self-location, may unite internal models self environment as soon enters brain.

Language: Английский

Citations

0
Olfactory bulb tracks breathing rhythms and place in freely behaving mice DOI Open Access
Scott C. Sterrett, Teresa M Findley,

Sidney E Rafilson

et al.

Published: March 11, 2025

Vertebrates sniff to control the odor samples that enter their nose. These can not only help identify odorous objects, but also locations and events. However, there is no receptor for place or time. Therefore, take full advantage of olfactory information, an animal’s brain must contextualize odor-driven activity with information about when, where, how they sniffed. To better understand contextual in system, we captured breathing movements mice while recording from bulb. In stimulus- task-free experiments, structure into persistent rhythmic states which are synchronous statelike ongoing neuronal population activity. reflect a strong dependence individual neuron on variation frequency, display using “sniff fields” quantify generalized linear models. addition, many bulb neurons have “place significant firing allocentric location, were comparable hippocampal recorded under same conditions. At level, mouse’s location be decoded similar accuracy hippocampus. Olfactory sensitivity cannot explained by rhythms scent marks. Taken together, show mouse tracks self-location, may unite internal models self environment as soon enters brain.

Language: Английский

Citations

0
Adaptive learning via BG-thalamo-cortical circuitry DOI Creative Commons
Qin He, Daniel N. Scott, Michael J. Frank

et al.

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

Published: March 13, 2025

People adjust their use of feedback over time through a process referred to as adaptive learning. We have recently proposed that the underlying mechanisms learning are rooted in how brain organizes into similarly credited units, which we refer latent states. Here develop BG-thalamo-cortical circuit model this and show it captures both commonalities heterogeneity human behavior. Our learns incrementally synaptic plasticity PFC-BG connections, but upon observing discordant information, produces thalamocortical reset signals alter PFC connectivity, driving attractor state transitions facilitate rapid updating behavioral policy. demonstrate mechanism can give rise optimized dynamics context either changepoints or reversals, under reasonable biological assumptions is able generalize efficiently across these conditions, adjusting behavior context-appropriate manner. Taken together, our results provide biologically plausible mechanistic for explains existing data makes testable predictions about computational roles different regions complex behaviors.

Language: Английский

Citations

0
Hierarchical behavioral analysis framework as a platform for standardized quantitative identification of behaviors DOI Creative Commons
Jialin Ye, Yang Xu, Kang Huang

et al.

Cell Reports, Journal Year: 2025, Volume and Issue: 44(2), P. 115239 - 115239

Published: Feb. 1, 2025

Language: Английский

Citations

0