22 papers · ranked by Valyu relevance
Jingting Liang, Sihoon Moon, Sahil Moza, Hyun Jee Lee + 6 more
Learning generates experience-dependent changes to the brain. However, how neurons of diverse functions and connectivity reorganize and modulate their activities to generate coherent changes while preserving essential functions is not well understood. Here, we address this question using an aversive olfactory learning…
M. J. Tilley, Michelle Miller, David A. Freedman
Biological neural networks are capable of recruiting different sets of neurons to encode different memories. However, when training artificial neural networks on a set of tasks, typically, no mechanism is employed for selectively producing anything analogous to these neuronal ensembles. Further, artificial neural…
Joao Barbosa, Remi Proville, Chris C. Rodgers, Srdjan Ostojic + 1 more
Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we propose that population gating…
Timo Flesch, Dávid Nagy, Andrew Saxe, Christopher Summerfield
Humans can learn several tasks in succession with minimal mutual interference but perform more poorly when trained on multiple tasks at once. The opposite is true for standard deep neural networks. Here, we propose novel computational constraints for artificial neural networks, inspired by earlier work on gating in the…
Timo Flesch, David G. Nagy, Andrew Saxe, Christopher Summerfield + 1 more
'Alireza Soltani'] Humans can learn several tasks in succession with minimal mutual interference but perform more poorly when trained on multiple tasks at once. The opposite is true for standard deep neural networks. Here, we propose novel computational constraints for artificial neural networks, inspired by earlier…
Sandeep Kumar, Anuj K. Sharma, Andrew M. Leifer
Title: Summary An animal’s current behavior influences its response to sensory stimuli, but the molecular and circuit-level mechanisms of this context-dependent decision-making are not well understood. Caenorhabditis elegans are less likely to respond to a mechanosensory stimulus by reversing if the stimuli is received…
Toshitake Asabuki, Prajakta Kokate, Tomoki Fukai, Abigail Morrison
The brain performs various cognitive functions by learning the spatiotemporal salient features of the environment. This learning requires unsupervised segmentation of hierarchically organized spike sequences, but the underlying neural mechanism is only poorly understood. Here, we show that a recurrent gated network of…
Zihan Qiu, Zekun Wang, Bo Zheng, Zeyu Huang + 9 more
Zihan Qiu ∗ 1 , Zekun Wang ∗ 1 , Bo Zheng ∗ 1 , Zeyu Huang ∗ 2 , Kaiyue Wen 3 , Songlin Yang 4 , Rui Men 1 , Le Yu 1 , Fei Huang 1 , Suozhi Huang 5 , Dayiheng Liu B 1 , Jingren Zhou 1 , Junyang Lin B 1 1Qwen Team, Alibaba Group 2University of Edinburgh 3Stanford University
Yoav Kessler, Sam Verschooren
A well-supported working memory (WM) model holds that a “gate” separates the content of WM from information that does not need to be maintained or manipulated. Previous research suggests that switching between opening and closing this gate incurs a response-time cost, reflecting controlled cognitive effort. However…
Joao Barbosa, Rémi Proville, Chris C. Rodgers, Michael R. DeWeese + 2 more
'Srdjan Ostojic' 'Yves Boubenec'] Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we…
Xiaohan Zhang, Mohamad Altrabulsi, Wenqi Xu, Ralf Wimmer + 2 more
The mammalian forebrain is the seat of higher cognition with architectural parallels to modern machine learning systems. Specifically, the cortex resembles recurrent neural networks (RNNs) while the thalamus resembles feedforward neural networks (FNNs). How such architectural features endow the forebrain with its…
Elizabeth L. Johnson, Jack J. Lin, David King-Stephens, Peter B. Weber + 6 more
'Peter B. Weber' 'Kenneth D. Laxer' 'Ignacio Saez' 'Fady Girgis' 'Mark D’Esposito' 'Robert T. Knight' 'David Badre'] Flexible behavior requires gating mechanisms that encode only task-relevant information in working memory. Extant literature supports a theoretical division of labor whereby lateral frontoparietal…
Aaron Traylor, Jack Merullo, Michael J. Frank, Ellie Pavlick
Trained on Human Working Memory Tasks Authors: ['Aaron Traylor' 'Jack Merullo' 'Michael J. Frank' 'Ellie Pavlick'] Models based on the Transformer neural network architecture have seen success on a wide variety of tasks that appear to require complex "cognitive branching"– or the ability to maintain pursuit of one goal…
Shaoli Wang, Tao Sheng, Feng Su, He Yang + 4 more
Acquired information can be consolidated to remote memory for storage but persists in a dormant state until its retrieval. However, it remains unknown how dormant memory is reactivated. Using a combination of simultaneous two-photon calcium imaging and holographic optogenetics in the anterior cingulate cortex (ACC) in…
Santiago Galella, Salva Ardid
Our brain can filter and integrate external information with internal representations to accomplish goal-directed behavior. The ability to switch between tasks effectively in response to context and external stimuli is a hallmark of cognitive control. Task switching occurs rapidly and efficiently, allowing us to…
Authors not listed
Early prediction of drug-induced organ toxicity remains a major bottleneck in drug discovery and clinical pharmacotherapy. Most data-driven toxicity models behave as endpoint predictors: they output a label but provide limited transparency about why a compound is risky or which evidence channel dominated the decision.…
Ke Zhang, Zhen Yang, Michael A. Gaffield, Garrett G. Gross + 2 more
Climbing fibers supervise cerebellar learning by providing signals to Purkinje cells (PCs) that instruct adaptive changes to mistakenly performed movements. Yet, climbing fibers are regularly active, even during well performed movements, suggesting that a mechanism dynamically regulates the ability of climbing fibers…
Bai, Qianyi, Wang Haiteng, Yu Qiang
While spiking neural networks (SNNs) provide a biologically inspired and energyefficient computational framework, their robustness and the dynamic advantages inherent to biological neurons remain significantly underutilized owing to oversimplified neuron models. In particular, conventional leaky integrate-and-fire…
W. Jeffrey Johnston, Stefano Fusi
The brain has large-scale modular structure in the form of brain regions, which are thought to arise from constraints on connectivity and the physical geometry of the cortical sheet. In contrast, experimental and theoretical work has argued both for and against the existence of specialized sub-populations of neurons…
Authors not listed
This paper formally defines an operational isomorphism between spectral damping in molecular vibronic systems and neuromodulatory control in biological sensory systems. Without asserting causal continuity or physical identity across scales, we show that both domains instantiate the same class of output-selective…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Authors not listed
The automatic generation of image captions in natural language is a critical and challenging task, particularly in the context of environmental monitoring and control. This paper presents a novel deep learning-driven image captioning system designed for real-time monitoring and predictive control of pollutant gas…