20 papers · ranked by Valyu relevance
Peter Cariani, Janet M. Baker
Here we present evidence for the ubiquity of fine spike timing and temporal coding broadly observed across sensory systems and widely conserved across diverse phyla, spanning invertebrates and vertebrates. A taxonomy of basic neural coding types includes channel activation patterns, temporal patterns of spikes, and…
Joy Bose
The Thousand Brains Theory (TBT) and its open-source Monty framework model object recognition through sensorimotor inference -- identifying objects by actively moving a sensor across their surface and building evidence contact by contact. The current implementation encodes each contact as a dense floating-point vector.…
Janet M. Baker, Peter Cariani
Time is essential for understanding the brain. A temporal theory for realizing major brain functions (e.g., sensation, cognition, motivation, attention, memory, learning, and motor action) is proposed that uses temporal codes, time-domain neural networks, correlation-based binding processes and signal dynamics. It…
Sam Post, William Mol, Noorhan Rahmatullah, Anubhuti Goel
Whether in music, language, baking, or memory, our experience of the world is fundamentally linked to time. However, it is unclear how temporal information is encoded, particularly in the range of milliseconds to seconds. Temporal processing at this scale is critical to prediction and survival, such as in a prey…
Byron H. Price, Jeffrey P. Gavornik
While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information…
Duho Sihn, Sung-Phil Kim
Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given…
Zahra M. Aghajan, Gabriel Kreiman, Itzhak Fried
The representation of time in the brain is a fundamental component of cognition. Here we investigated how the human brain represents time during a temporally continuous uninterrupted experience by presenting fifteen neurosurgical patients with an audiovisual video while recording neurons’ activity from multiple brain…
Anna Cattani, Gaute T. Einevoll, Stefano Panzeri
The phase-of-firing code is a neural coding scheme whereby neurons encode information using the time at which they fire spikes within a cycle of the ongoing oscillatory pattern of network activity. This coding scheme may allow neurons to use their temporal pattern of spikes to encode information that is not encoded in…
Zihan Pan, Jibin Wu, Malu Zhang, Haizhou Li + 1 more
—Neural encoding plays an important role in faithfully describing the temporally rich patterns, whose instances include human speech and environmental sounds. For tasks that involve classifying such spatio-temporal patterns with the Spiking Neural Networks (SNNs), how these patterns are encoded directly influence the…
Anthony Stigliani, Brianna Jeska, Kalanit Grill-Spector
How does high-level visual cortex process temporal aspects of our visual experience? By modeling neural responses with millisecond precision in separate sustained and transient channels, we predict fMRI responses for stimuli ranging from 33 ms to 20 s. Using this approach, we discovered that lateral temporal regions…
Gabriel M. Stine, Mehrdad Jazayeri
Cognition unfolds dynamically over flexible timescales. A major goal of the field is to understand the computational and neurobiological principles that enable this flexibility. Here, we argue that the neurobiology of timing provides a platform for tackling these questions. We begin with an overview of proposed coding…
Sophie Bagur, Jacques Bourg, Alexandre Kempf, Thibault Tarpin + 7 more
The brain constantly associates time-varying sensory inputs with behavioral decisions. However, how temporal information in sensory neuronal circuits is linked to perception and behavioral output remains unclear. Here, by training mice to categorize patterned optogenetic stimulations in the auditory cortex, we show…
Héctor Díaz, Lucas Bayones, Manuel Alvarez, Bernardo Andrade-Ortega + 4 more
Understanding how time perception adapts to cognitive demands remains a significant challenge. In some contexts, the brain encodes time categorically (as “long” or “short”), while in others, it encodes precise time intervals on a continuous scale. Although the ventral premotor cortex (VPC) is known for its role in…
Myoung Won Cho, Moo Young Choi
Pattern coding is a general concept for neural coding, which indicates that the objective meaning of information can be represented by spatio-temporal firing patterns of a group of neurons [1]. We introduce a feasible way through which spatio-temporal firing patterns represent complex information systematically.…
Kacie Lee, Reuben Rideaux
Past sensory experiences influence perception of the present. Multiple research subfields have emerged to study this phenomenon at different temporal scales. These phenomena fall into three categories: the influence of immediately preceding sensory events (micro), expectations established by short sequences of events…
Lopez-Randulfe, Javier, Reeb, Nico + 2 more
Processing sensor data with spiking neural networks on digital neuromorphic chips requires converting continuous analog signals into spike pulses. Two strategies are promising for achieving low energy consumption and fast processing speeds in end-to-end neuromorphic applications. First, to directly encode analog…
Jared M. Salisbury, Stephanie E. Palmer
Almost all neural computations involve making predictions. Whether an organism is trying to catch prey, avoid predators, or simply move through a complex environment, the data it collects through its senses can guide its actions only to the extent that it can extract from these data information about the future state…
Fuzhan Rahmanian, Robert M. Lee, Dominik Linzner, Kathrin Michel + 4 more
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation paths, form factors, and electrochemical testing protocols. Existing models typically translate poorly across different electrode, electrolyte, and additive materials, mostly require a fixed…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
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…