25 papers · ranked by Valyu relevance
Oak E. Milam, Gary Marsat, Stephen D. Ginsberg
Localizing the source of a signal requires sophisticated neural mechanisms, and we are still uncovering the coding principles that support accurate spatial processing. Weakly electric fish can detect and localize distant conspecifics, but the way this spatial information is encoded is unclear. Here, we investigate the…
Jean Simonnet, Michael Brecht
The subiculum is the major output structure of the hippocampal formation and is involved in learning and memory as well as in spatial navigation. Little is known about how the cellular diversity of subicular neurons is related to function. Primed by in vitro studies, which identified distinct bursting patterns in…
Ladan Yang, Catherine Mikkelsen
The hippocampus has been associated with spatial information processing (30). However, it is also not clear whether such ensemble coding of spatial information extends to other brain regions in the medial temporal lobe. Hence, this study uses various classification techniques to attempt to decode spatial and valence…
Udaysankar Chockanathan, Krishnan Padmanabhan
Molecular, anatomic, and behavioral studies show that the hippocampus is structurally and functionally heterogeneous, with dorsal hippocampus implicated in mnemonic processes and spatial navigation and ventral hippocampus involved in affective processes. By performing electrophysiological recordings of large neuronal…
Jean Simonnet, Michael Brecht
The subiculum is the major output structure of the hippocampal formation and is involved in learning and memory as well as in spatial navigation. Little is known about how neuronal diversity contributes to function in the subiculum. Previously, in vitro studies have identified distinct bursting patterns in the…
Christian Balkenius, Peter Gärdenfors
Spaces in the brain can refer either to psychological spaces, which are derived from similarity judgments, or to neurocognitive spaces, which are based on the activities of neural structures. We want to show how psychological spaces naturally emerge from the underlying neural spaces by dimension reductions that…
Shane M. O’Mara, John P. Aggleton
Memory research remains focused on just a few brain structures-in particular, the hippocampal formation (the hippocampus and entorhinal cortex). Three key discoveries promote this continued focus: the striking demonstrations of enduring anterograde amnesia after bilateral hippocampal damage; the realization that…
Lingyun Ke, M. Hu
Encoding static images into spike trains is a crucial step for enabling Spiking Neural Networks (SNNs) to process visual information efficiently. However, existing schemes such as rate coding, Poisson encoding, and time-to-first-spike (TTFS) often ignore spatial relationships and yield temporally inconsistent spike…
Christine M. Lykken, Benjamin R. Kanter, Anne Nagelhus, Jordan Carpenter + 3 more
A systems-level understanding of cortical computation requires insight into how neural codes are transformed across distinct brain circuits. In the mammalian cortex, one of the few systems where such transformations are tractable is the spatial mapping circuit. This circuit comprises interconnected regions of medial…
Oliver Baumann, Jason B. Mattingley
It is generally accepted that spatial relationships and spatial information are critically involved in the formation of cognitive maps. It remains unclear, however, which properties of the world are explicitly encoded and how these properties might contribute to the formation of such maps. It has been proposed that…
Yanbo Lian, Anthony N. Burkitt
Cells in the entorhinal cortex (EC) contain rich spatial information and project strongly to the hippocampus where a cognitive map is supposedly created. These cells range from cells with structured spatial selectivity, such as grid cells in the medial EC (MEC) that are selective to an array of spatial locations that…
Cynthia Rais, Maxime Maheu, J. Simon Wiegert
Neuronal representations of the world are dynamic. A striking example is the rapid remapping of the hippocampal spatial code, which occurs even when the environment and behavior remain unchanged. CA3 input to CA1 has been shown to exert a key role in triggering synaptic plasticity in place-encoding CA1 cells — a…
Robert Worden
Animals build an internal Bayesian maximum likelihood model of the local 3-D space around them. This 3-D model is essential for controlling all physical movements. There has been large and sustained selection pressure to make it the most precise model possible, given the animal's sense data. A tracking computation has…
Sean Knight
Spatial learning across many species is impaired by lesions in the hippocampus, a subcortical brain structure whose cellular composition changes substantially over its 5-6 week lifetime from mainly excitatory neurons during development to equal proportions of inhibitory interneurons (gamma-Amp/Arcs) as well as…
David Schwartz, O. Ozan Koyluoglu
Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that form a periodic and hexagonal tiling of the environment. The joint activity of…
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…
Chance J. Hamilton, Alfredo Weitzenfeld
This paper presents the Visual Place Cell Encoding (VPCE) model, a biologically inspired computational framework for simulating place cell–like activation using visual input. Drawing on evidence that visual landmarks play a central role in spatial encoding, the proposed VPCE model activates visual place cells by…
Kristjan Kalm, Dennis Norris
Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation…
Kate J. Jeffery
The cognitive map, proposed by Tolman in the 1940s, is a hypothetical internal representation of space constructed by the brain to enable an animal to undertake flexible spatial behaviors such as navigation. The subsequent discovery of place cells in the hippocampus of rats suggested that such a map-like representation…
Julien Dupeyroux
— The third generation of artificial intelligence (AI) introduced by neuromorphic computing is revolutionizing the way robots and autonomous systems can sense the world, process the information, and interact with their environment. The promises of high flexibility, energy efficiency, and robustness of neuromorphic…
Kevin Q Shan, Evgueniy V Lubenov, Maria Papadopoulou, Athanassios G Siapas + 1 more
'Athanassios G Siapas' 'Michael Häusser'] The hippocampus is a brain area crucial for episodic memory in humans. In contrast, studies in rodents have highlighted its role in spatial learning, supported by the discovery of place cells. Efforts to reconcile these views have found neurons in the rodent hippocampus that…
J. Gerard Wolff
The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits…
Spencer Kim, Dylan Gray, Michelle Shanguhyia, Rachel Steinhardt
Recreating the signaling profile a chemical synapse to analyze serotonin receptor activation is a challenge. This is due in part to the kinetics of the synapse, where neurotransmitters are rapidly released and quickly cleared by active reuptake machinery. One strategy to produce a rapid rise in a bio-orthogonally…
Authors not listed
Real-world datasets in chemical engineering and bioengineering processes--such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials--can often be unlabelled or disorganized, rendering the training of existing supervised learning models ineffective at learning the…
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…