Decoding Neural Activity of the Simplest Heterogeneous Neural Networks DOI
Galiya M. Markova, С. И. Барцев

Опубликована: Янв. 1, 2024

Язык: Английский

A transient high-dimensional geometry affords stable conjunctive subspaces for efficient action selection DOI Creative Commons
Atsushi Kikumoto, Apoorva Bhandari, Kazuhisa Shibata

и другие.

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

4

Robustness of working memory to prefrontal cortex microstimulation DOI Creative Commons
Joana Soldado-Magraner,

Yuki Minai,

Byron M. Yu

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 14, 2025

Delay period activity in the dorso-lateral prefrontal cortex (dlPFC) has been linked to maintenance and control of sensory information working memory. The stability memory related signals found such delay is believed support robust memory-guided behavior during perturbations, as distractors. Here, we directly probed dlPFC's with a diverse set measured their consequences on neural behavior. We applied patterned microstimulation dlPFC monkeys implanted multi-electrode arrays by electrically stimulating different electrodes array while performed saccade task. that perturbations affected spatial memory-related individual neurons. However, task performance remained largely unaffected. These apparently contradictory observations could be understood examining dimensions population activity. In where naturally evolved over time, impacted contrast, containing were stable minimally This dissociation explained how stably maintained despite changes induced microstimulation. Thus, processes are variety dlPFC. Memory-guided remarkably distractions. underlie this robustness, given it maintains presence sought understand extent which circuits can robustly maintain was dlPFC, widespread caused perturbations. Our findings indicate direct an ability may due mediate similar robustness face distraction.

Язык: Английский

Процитировано

0

Decoding Neural Activity of the Simplest Heterogeneous Neural Networks DOI
Galiya M. Markova, С. И. Барцев

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 362 - 371

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

The dominoes of features: Dynamic sequential refinement of working memory representations DOI
Shengyuan Wang,

Xiaoying Min,

Xiaowei Ding

и другие.

Cognition, Год журнала: 2025, Номер 260, С. 106133 - 106133

Опубликована: Апрель 6, 2025

Язык: Английский

Процитировано

0

Neural dynamics of visual working memory representation during sensory distraction DOI Open Access
Jonas Karolis Degutis, Simon Weber, Joram Soch

и другие.

Опубликована: Апрель 11, 2025

Recent studies have provided evidence for the concurrent encoding of sensory percepts and visual working memory contents (VWM) across areas; however, it has remained unclear how these two types representations are concurrently present. Here, we reanalyzed an open-access fMRI dataset where participants memorized a stimulus while simultaneously being presented with distractors. First, found that VWM code in several regions did not fully generalize between different time points, suggesting dynamic code. A more detailed analysis revealed this was due to shifts coding spaces time. Second, collapsed neural signals assess degree interference distractors, specifically by testing alignment their spaces. We find feature-matching distractors encoded do overlap, but separation decreases when negatively impact behavioral performance recalling target. Together, results indicate role temporally stable helping multiplex perception within areas.

Язык: Английский

Процитировано

0

Neural dynamics of visual working memory representation during sensory distraction DOI Open Access
Jonas Karolis Degutis, Simon Weber, Joram Soch

и другие.

Опубликована: Авг. 27, 2024

Recent studies have provided evidence for the concurrent encoding of sensory percepts and visual working memory contents (VWM) across areas; however, it has remained unclear how these two types representations are concurrently present. Here, we reanalyzed an open-access fMRI dataset where participants memorized a stimulus while simultaneously being presented with distractors. First, found that VWM code in several regions did not generalize well between different time points, suggesting dynamic code. A more detailed analysis revealed this was due to shifts coding spaces time. Second, collapsed neural signals assess degree interference distractors, specifically by testing alignment their spaces. We find feature-matching distractors encoded separable Together, results indicate role temporally stable helping multiplex perception within areas.

Язык: Английский

Процитировано

3

A Transient High-dimensional Geometry Affords Stable Conjunctive Subspaces for Efficient Action Selection DOI Creative Commons
Atsushi Kikumoto, Apoorva Bhandari, Kazuhisa Shibata

и другие.

Опубликована: Июнь 11, 2023

Abstract Flexible action selection requires cognitive control mechanisms capable of mapping the same inputs to different output actions depending on context. From a neural state-space perspective, this representation that separates similar input states by Additionally, for be robust and time-invariant, information must stable in time, enabling efficient readout. Here, using EEG decoding methods, we investigate how geometry dynamics representations constrain flexible human brain. Participants performed context-dependent task. A forced response procedure probed trajectories. The result shows before successful responses, there is transient expansion representational dimensionality separated conjunctive subspaces. Further, stabilizes time window, with entry into stable, high-dimensional state predictive individual trial performance. These results establish brain needs over behavior.

Язык: Английский

Процитировано

9

Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model DOI Creative Commons
Klavdia Zemlianova, Amitabha Bose, John Rinzel

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Ноя. 2, 2024

Despite music's omnipresence, the specific neural mechanisms responsible for perceiving and anticipating temporal patterns in music are unknown. To study potential keeping time rhythmic contexts, we train a biologically constrained RNN, with excitatory (E) inhibitory (I) units, on seven different stimulus tempos (2–8 Hz) synchronization continuation task, standard experimental paradigm. Our trained RNN generates network oscillator that uses an input current (context parameter) to control oscillation frequency replicates key features of dynamics observed recordings monkeys performing same task. We develop reduced three-variable rate model analyze its dynamic properties. By treating our understanding mathematical structure oscillations as predictive, confirm dynamical found also RNN. neurally plausible reveals E-I circuit two distinct sub-populations, which one is tightly synchronized units.

Язык: Английский

Процитировано

2

Re-evaluating human MTL in working memory: insights from intracranial recordings DOI
Jin Li, Dan Cao, Wenlu Li

и другие.

Trends in Cognitive Sciences, Год журнала: 2024, Номер 28(12), С. 1132 - 1144

Опубликована: Авг. 23, 2024

Язык: Английский

Процитировано

1

Neural dynamics of visual working memory representation during sensory distraction DOI Creative Commons
Jonas Karolis Degutis, Simon Weber, Joram Soch

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Апрель 15, 2024

Abstract Recent studies have provided evidence for the concurrent encoding of sensory percepts and visual working memory contents (VWM) across areas; however, it has remained unclear how these two types representations are concurrently present. Here, we reanalyzed an open-access fMRI dataset where participants memorized a stimulus while simultaneously being presented with distractors. First, found that VWM code in several regions did not generalize well between different time points, suggesting dynamic code. A more detailed analysis revealed this was due to shifts coding spaces time. Second, collapsed neural signals assess degree interference distractors, specifically by testing alignment their spaces. We find feature-matching distractors encoded separable Together, results indicate role temporally stable helping multiplex perception within areas.

Язык: Английский

Процитировано

0