Context changes retrieval of prospective outcomes during decision deliberation DOI Creative Commons
Pinar Göktepe-Kavis, Florence M. Aellen, Aurelio Cortese

et al.

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(12)

Published: Dec. 1, 2024

Foreseeing the future outcomes is art of decision-making. Substantial evidence shows that, during choice deliberation, brain can retrieve prospective decision outcomes. However, decisions are seldom made in a vacuum. Context carries information that radically affect choice. Nevertheless, most investigations retrieval processes examined isolation, disregarding context which they occur. Here, we studied how shapes outcome deliberation. We designed decision-making task where participants were presented with object-context pairs and led to certain outcome. show likely retrieved transient patterns neural activity, as early 3 s before decided. The strength explains participants' behavioral efficiency, but only when affects Our results suggest imparts strong constraints on representations shaped

Language: Английский

The homogenous hippocampus: How hippocampal cells process available and potential goals DOI Creative Commons
Neil McNaughton, David M. Bannerman

Progress in Neurobiology, Journal Year: 2024, Volume and Issue: 240, P. 102653 - 102653

Published: July 2, 2024

We present here a view of the firing patterns hippocampal cells that is contrary, both functionally and anatomically, to conventional wisdom. argue hippocampus responds efference copies goals encoded elsewhere; it uses these detect resolve conflict or interference between in general. While can involve space, do not encode spatial (or other special types of) memory, as such. also transverse circuits operate an essentially homogeneous way along its length. The apparently different functions parts (e.g. memory retrieval versus anxiety) result from (situational/motivational) inputs on which those perform same fundamental computational operations. On this view, key role iterative adjustment, via Papez-like circuits, synaptic weights cell assemblies elsewhere.

Language: Английский

Citations

25
Abstract representations emerge in human hippocampal neurons during inference DOI Creative Commons
Hristos Courellis, Juri Minxha, Araceli R. Cardenas

et al.

Nature, Journal Year: 2024, Volume and Issue: 632(8026), P. 841 - 849

Published: Aug. 14, 2024

Humans have the remarkable cognitive capacity to rapidly adapt changing environments. Central this is ability form high-level, abstract representations that take advantage of regularities in world support generalization1. However, little known about how these are encoded populations neurons, they emerge through learning and relate behaviour2,3. Here we characterized representational geometry neurons (single units) recorded hippocampus, amygdala, medial frontal cortex ventral temporal neurosurgical patients performing an inferential reasoning task. We found only neural formed hippocampus simultaneously encode several task variables abstract, or disentangled, format. This uniquely observed after learn perform inference, consists disentangled directly observable discovered latent variables. Learning inference by trial error verbal instructions led formation hippocampal with similar geometric properties. The relation between format behaviour suggests geometries important for complex cognition. A which participants learned whose properties reflected structure task, indicating

Language: Английский

Citations

18
A goal-centric outlook on learning DOI Creative Commons
Gaia Molinaro, Anne Collins

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(12), P. 1150 - 1164

Published: Sept. 9, 2023

Language: Английский

Citations

30
Neural representation in active inference: Using generative models to interact with—and understand—the lived world DOI
Giovanni Pezzulo, Leo D’Amato, Francesco Mannella

et al.

Annals of the New York Academy of Sciences, Journal Year: 2024, Volume and Issue: 1534(1), P. 45 - 68

Published: March 25, 2024

Abstract This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that learns navigate world adaptively, not (or solely) understand it. Different may possess an array models, spanning from those support action‐perception cycles underwrite planning imagination; namely, explicit entail variables predicting concurrent sensations, like objects, faces, or people—to action‐oriented predict action outcomes. then elucidates belief dynamics might link implications different types agent's cognitive capabilities in relation its ecological niche. concludes open questions regarding evolution development advanced abilities—and gradual transition pragmatic detached representations. on offer foregrounds diverse roles play processes representation.

Language: Английский

Citations

12
Exploring the role of dimensionality transformation in episodic memory DOI Creative Commons
Casper Kerrén, Daniel Reznik, Christian F. Doeller

et al.

Trends in Cognitive Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Episodic memory must accomplish two adversarial goals: encoding and storing a multitude of experiences without exceeding the finite neuronal structure brain, recalling memories in vivid detail. Dimensionality reduction expansion ('dimensionality transformation') enable brain to meet these demands. Reduction compresses sensory input into simplified, storable codes, while reconstructs details. Although processes are essential memory, their neural mechanisms for episodic remain unclear. Drawing on recent insights from cognitive psychology, systems neuroscience, neuroanatomy, we propose accounts how dimensionality transformation occurs brain: structurally (via corticohippocampal pathways) functionally (through oscillations). By examining cross-species evidence, highlight that may support identify crucial questions future research.

Language: Английский

Citations

1
Building compositional tasks with shared neural subspaces DOI Creative Commons
Sina Tafazoli, Flora Bouchacourt, Adel Ardalan

et al.

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

Published: Feb. 1, 2024

Cognition is remarkably flexible; we are able to rapidly learn and perform many different tasks

Language: Английский

Citations

7
Mental search of concepts is supported by egocentric vector representations and restructured grid maps DOI Creative Commons
Simone Viganò, Rena Bayramova, Christian F. Doeller

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Dec. 8, 2023

Abstract The human hippocampal-entorhinal system is known to represent both spatial locations and abstract concepts in memory the form of allocentric cognitive maps. Using fMRI, we show that parietal cortex evokes complementary egocentric representations conceptual spaces during goal-directed mental search, akin those observable physical navigation determine where a goal located relative oneself (e.g., our left or right). Concurrently, strength grid-like signal, neural signature maps entorhinal, prefrontal, cortices, modulated as function proximity space. These brain mechanisms might support flexible parallel readout target information stored memory, capitalizing on reference frames.

Language: Английский

Citations

14
Abstract representations emerge in human hippocampal neurons during inference behavior DOI Open Access
Hristos Courellis,

Juri Mixha,

Araceli R. Cardenas

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 11, 2023

Abstract Humans have the remarkable cognitive capacity to rapidly adapt changing environments. Central this is ability form high-level, abstract representations that take advantage of regularities in world support generalization 1 . However, little known about how these are encoded populations neurons, they emerge through learning, and relate behavior 2,3 Here we characterized representational geometry neurons (single-units) recorded hippocampus, amygdala, medial frontal cortex, ventral temporal cortex neurosurgical patients who performing an inferential reasoning task. We find only neural formed hippocampus simultaneously encode multiple task variables abstract, or disentangled, format. This uniquely observed after learn perform inference, consisted disentangled directly observable discovered latent variables. Interestingly, learning inference by trial error verbal instructions led formation hippocampal with similar geometric properties. The relation between format suggests abstract/disentangled geometries important for complex cognition.

Language: Английский

Citations

10
Impoverished details with preserved gist in remote and recent spatial memory following hippocampal and fornix lesions DOI
Adrienne Li, Xuehui Lei, Katherine A. Herdman

et al.

Neuropsychologia, Journal Year: 2024, Volume and Issue: 194, P. 108787 - 108787

Published: Jan. 5, 2024

Language: Английский

Citations

3
Expectancy-related changes in firing of dopamine neurons depend on hippocampus DOI Creative Commons
Zhewei Zhang, Yuji K. Takahashi,

Marlian Montesinos-Cartegena

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Oct. 16, 2024

The orbitofrontal cortex (OFC) and hippocampus (HC) both contribute to the cognitive maps that support flexible behavior. Previously, we used dopamine neurons measure functional role of OFC. We recorded midbrain as rats performed an odor-based choice task, in which expected rewards were manipulated across blocks. found ipsilateral OFC lesions degraded dopaminergic prediction errors, consistent with reduced resolution task states. Here have repeated this experiment male HC lesions. results show also shapes states, however unlike OFC, provides information local trial, is necessary for estimating upper-level hidden states distinguish contrast roles mapping suggest access rich from distributed regions regarding environment's structure, potentially enabling teaching signal complex behaviors.

Language: Английский

Citations

3