18 papers · ranked by Valyu relevance
Ying Zhou, Clayton E. Curtis, Daryl Fougnie, Kartik K. Sreenivasan
Models of working memory make fundamentally different commitments to the architecture of individual memories. Information-sparse models conceptualize individual memories single point estimates agnostic to meta-cognitive variables such a uncertainty. In contrast, information-rich models propose memories re encoded s…
Ying Zhou, Clayton E. Curtis, Daryl Fougnie, Kartik K. Sreenivasan
Models of working memory make fundamentally different commitments to the architecture of individual memories. Information-sparse models conceptualize individual memories as single point estimates agnostic to meta-cognitive variables such as uncertainty. In contrast, information-rich models propose memories are encoded…
Michaël Vanhoyland, Peter Janssen, Tom Theys
Conscious perception, a critical aspect of human cognition, is assumed to emerge from a complex network of interacting brain regions that transmit information via feedforward and recurrent pathways. This study presents single- and multiunit recordings from the human lateral occipital complex (LO), a key region for…
Adam Hockley, Connor G Gallimore, Jordan P Hamm, Manuel S Malmierca
Context modulates neural processing of sensory stimuli. Neural responses are suppressed to stimuli that are typical in their context and augmented to stimuli that deviate from their context. The latter has been conceptualized as a “prediction error”, which can serve to enhance the salience, direct attention, or support…
Ghahari, Azar, Eden, Uri T.
In the last decade, there have been major advances in clusterless decoding algorithms for neural data analysis. These algorithms use the theory of marked point processes to describe the joint activity of many neurons simultaneously, without the need for spike sorting. In this study, we examine information-theoretic…
Xin Huang, Bikalpa Ghimire, Anjani Sreeprada Chakrala, Steven Wiesner + 2 more
Motion speed is a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains unclear. Here, we investigated the encoding and decoding of multiple speeds. We first characterized the perceptual capacity of human and macaque subjects to segment overlapping stimuli…
H. Fareed Ahmed, Toktam Samiei, Erfan Nozari
Although neural activity is organized across multiple temporal and spatial scales, the principles determining information representation across scales remain unclear. In particular, while recent empirical results have reported mesoscale optimality in neural decoding, no theoretical accounts exist that can explain when…
Danilo Benozzo, Lorenzo Ferrucci, Francesco Ceccarelli, Aldo Genovesio
Multiple history biases affect our representation of magnitudes, such as time, distance and size. It is not clear whether the previous stimuli interfere with the discrimination process from the moment of stimulus presentation, during working memory retention or even later during the decision-making phase. We used a…
John R. Minnick, Jesus Gonzalez-Ferrer, Kamran Hussain, Jinghui Geng + 5 more
Closed-loop brain-computer interfaces often require both a forecast of upcoming neural population activity and a readout of the animal's behavioral state. A single Mamba forecaster, trained only on next-step spike counts at Neuropixels scale, can deliver both in one forward pass. A lightweight per-session linear head…
H. Fareed Ahmed, Toktam Samiei, Erfan Nozari
A unique feature, and challenge, in comparing decoding accuracies across scales is the potentially confounding effects of dimensionality. Unlike most machine learning problems where feature dimensions are either fixed or variable independently of the choice of model (due to missing data, e.g.), here the dimension of…
Stefano Panzeri, Nicola Marie Engel, Marco Celotto
The publication of Mainen and Sejnowski’s 1995 seminal paper strongly renewed interest in how spike timing contributes to the neural code. In the 3 decades since then, considerable experimental and theoretical research has investigated the timescales at which spike timing contributes to the neural code. Here we review…
Woojae Jeong, Wenhui Cui, Kleanthis Avramidis, Takfarinas Medani + 2 more
Electroencephalography (EEG) offers detailed access to neural dynamics but remains constrained by noise and trialby-trial variability, limiting decoding performance in datarestricted or complex paradigms. Data augmentation is often employed to enhance feature representations, yet conventional uniform averaging…
Daniel Anthes, Sushrut Thorat, Anna Mitola, Paolo Papale + 2 more
In studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regions in a stage-like fashion in an effort to extract high-level information from the retinal input. Consequently, electrophysiological…
Esteban Félez Martínez, Filippo Costa, Debora Ledergerber, Lukas Imbach + 2 more
Composing individual memory traces into unified representations is fundamental to encoding of structured relationships and flexible cognition. A central debate in neuroscience concerns the neural mechanisms of these compositions: are these compositions encoded through mixed selectivity, where the same neurons…
Huanqiu Zhang, Israel Nelken, Tatyana Sharpee
Deciphering the neural code requires identifying its fundamental symbols or code-words. Neural activity is usually interpreted either as a rate code – based on average spike counts – or as a temporal code, which distinguishes patterns with identical counts. Yet, the symbols of the code remain undefined. Here we show…
Ori Hendler, Ronen Segev, Maoz Shamir
Sensory information propagates through successive processing stages in the brain, where synaptic weight patterns between stations determine how downstream neurons decode information from upstream populations. Although optimized synaptic connectivity can enhance information transmission, it requires precise weight…
Nambu Yoshihiro
We propose a practical hybrid decoding scheme for the parity-encoding architecture. This architecture was first introduced by N. Sourlas as a computational technique for tackling hard optimization problems, especially those modeled by spin systems such as the Ising model and spin glasses, and reinvented by W. Lechner…
María Peña Fernández, Lara Lloret Iglesias, Jesús Marco de Lucas
How much machinery does a network need to memorize and recall discrete sequences when constrained to a biologically plausible substrate? We address this question using 50 short monophonic melodies in 4/4, used only as a controlled sequence-memory benchmark. Each beat is encoded with two clean one-hot populations – a…