Active reconfiguration of neural task states DOI Creative Commons
Harrison Ritz, Aditi Jha, Jonathan W. Pillow

и другие.

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

Опубликована: Сен. 30, 2024

The ability to switch between different tasks is a core component of adaptive cognition, but mechanistic understanding this capacity has remained elusive. Longstanding questions over whether task switching requires active preparation remain hotly contested, in large part due the difficulty inferring preparatory dynamics from behavior or time-locked neuroimaging. We make progress on debate by quantifying neural representations using high-dimensional linear dynamical systems fit human electroencephalographic recordings. find that these have high predictive accuracy and reveal signatures are shared with task-optimized networks. These findings inform classic about how we control our offer promising new paradigm for neuroimaging analysis.

Язык: Английский

Neural population geometry: An approach for understanding biological and artificial neural networks DOI Creative Commons
SueYeon Chung,

L. F. Abbott

Current Opinion in Neurobiology, Год журнала: 2021, Номер 70, С. 137 - 144

Опубликована: Окт. 1, 2021

Advances in experimental neuroscience have transformed our ability to explore the structure and function of neural circuits. At same time, advances machine learning unleashed remarkable computational power artificial networks (ANNs). While these two fields different tools applications, they present a similar challenge: namely, understanding how information is embedded processed through high-dimensional representations solve complex tasks. One approach addressing this challenge utilize mathematical analyze geometry representations, i.e., population geometry. We review examples geometrical approaches providing insight into biological networks: representation untangling perception, geometric theory classification capacity, disentanglement abstraction cognitive systems, topological underlying maps, dynamic motor dynamical cognition. Together, findings illustrate an exciting trend at intersection learning, neuroscience, geometry, which provides useful population-level mechanistic descriptor task implementation. Importantly, descriptions are applicable across sensory modalities, brain regions, network architectures timescales. Thus, has potential unify networks, bridging gap between single neurons, populations behavior.

Язык: Английский

Процитировано

204
50 years of mnemonic persistent activity: quo vadis? DOI Creative Commons
Xiao‐Jing Wang

Trends in Neurosciences, Год журнала: 2021, Номер 44(11), С. 888 - 902

Опубликована: Окт. 13, 2021

Язык: Английский

Процитировано

79
Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior DOI Creative Commons
Takuya Ito, Guangyu Robert Yang,

Patryk A. Laurent

и другие.

Nature Communications, Год журнала: 2022, Номер 13(1)

Опубликована: Фев. 3, 2022

Abstract The human ability to adaptively implement a wide variety of tasks is thought emerge from the dynamic transformation cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in “conjunction hubs”—brain regions selectively integrate sensory, cognitive, and motor activations. used recent advances using functional connectivity map flow activity between brain construct task-performing neural network model fMRI data during control task. verified importance conjunction hubs computations by simulating over this empirically-estimated model. These empirically-specified simulations produced above-chance task performance (motor responses) integrating sensory rule hubs. findings reveal role supporting flexible computations, while demonstrating feasibility models gain insight into brain.

Язык: Английский

Процитировано

43
The computational foundations of dynamic coding in working memory DOI Creative Commons
Jake P. Stroud, John Duncan, Máté Lengyel

и другие.

Trends in Cognitive Sciences, Год журнала: 2024, Номер 28(7), С. 614 - 627

Опубликована: Апрель 4, 2024

Working memory (WM) is a fundamental aspect of cognition. WM maintenance classically thought to rely on stable patterns neural activities. However, recent evidence shows that population activities during undergo dynamic variations before settling into pattern. Although this has been difficult explain theoretically, network models optimized for typically also exhibit such dynamics. Here, we examine versus coding in data, classical models, and task-optimized networks. We review principled mathematical reasons why do not, while naturally coding. suggest an update our understanding maintenance, which computational feature rather than epiphenomenon.

Язык: Английский

Процитировано

18
Ketamine induces multiple individually distinct whole-brain functional connectivity signatures DOI Creative Commons
Flora Moujaes, Jie Lisa Ji, Masih Rahmati

и другие.

eLife, Год журнала: 2024, Номер 13

Опубликована: Апрель 17, 2024

Background: Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it unclear how ketamine’s molecular mechanisms connect its neural behavioral effects. Methods: We conducted a single-blind placebo-controlled study, with participants blinded their treatment condition. 40 healthy received acute (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). quantified resting-state functional connectivity via data-driven global brain related individual ketamine-induced symptom variation cortical gene expression targets. Results: found that: (i) both effects are multi-dimensional, reflecting robust variability; (ii) principal gradient effect matched somatostatin (SST) parvalbumin (PVALB) patterns humans, while mean did not; (iii) mapped onto distinct gradients ketamine, which were resolvable at single-subject level. Conclusions: These results highlight importance considering ketamine. They also have implications development individually precise pharmacological biomarkers selection psychiatry. Funding: This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 R01MH112746 (J.D.M.), 5R01MH112189 5R01MH108590 NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex 2015276 (J.D.M.); Brain Behavior Research Foundation Young Investigator Award SFARI Pilot (J.D.M., A.A.); Heffter Institute (Grant No. 1–190420) (FXV, KHP); Swiss Neuromatrix 2016–0111) National Science under framework Neuron Cofund 01EW1908) (KHP); Usona (2015 – 2056) (FXV). Clinical trial number: NCT03842800

Язык: Английский

Процитировано

9
Maintenance and transformation of representational formats during working memory prioritization DOI Creative Commons
Daniel Pacheco, Marie-Christin Fellner, Lukas Kunz

и другие.

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

Опубликована: Сен. 19, 2024

Язык: Английский

Процитировано

6
Comparing representations and computations in single neurons versus neural networks DOI
Camilo Libedinsky

Trends in Cognitive Sciences, Год журнала: 2023, Номер 27(6), С. 517 - 527

Опубликована: Апрель 1, 2023

Язык: Английский

Процитировано

10
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
Intermittent rate coding and cue-specific ensembles support working memory DOI Creative Commons
Matthew F. Panichello, Donatas Jonikaitis,

Yu jin Oh

и другие.

Nature, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 6, 2024

Abstract Persistent, memorandum-specific neuronal spiking activity has long been hypothesized to underlie working memory 1,2 . However, emerging evidence suggests a potential role for ‘activity-silent’ synaptic mechanisms 3–5 This issue remains controversial because either view largely relied on datasets that fail capture single-trial population dynamics or indirect measures of spiking. We addressed this controversy by examining the mnemonic information single trials obtained from large, local populations lateral prefrontal neurons recorded simultaneously in monkeys performing task. Here we show does not persist during delays, but instead alternates between coordinated ‘On’ and ‘Off’ states. At level neurons, Off states are driven both loss selectivity memoranda return firing rates spontaneous levels. Further exploiting large-scale recordings used here, is available patterns functional connections among ensembles Our results suggest intermittent periods coexist with support memory.

Язык: Английский

Процитировано

4
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