scholarly journals Independent Neural Activity Patterns for Sensory- and Confidence-Based Information Maintenance during Category-Selective Visual Processing

eNeuro ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. ENEURO.0268-18.2018 ◽  
Author(s):  
Matthew D. Weaver ◽  
Johannes J. Fahrenfort ◽  
Artem Belopolsky ◽  
Simon van Gaal
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Activity Patterns

scholarly journals Sequence learning recodes cortical representations instead of strengthening initial ones

2018 ◽  
Author(s):  
Kristjan Kalm ◽  
Dennis Norris
Keyword(s):  
Neural Activity ◽  
Sequence Learning ◽  
Visual Processing ◽  
Computational Models ◽  
Activity Patterns ◽  
Recall Task ◽  
Neural Representation ◽  
Processing Stream ◽  
Initial Sequence ◽  
Cortical Representations

AbstractWe contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patters from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations.

scholarly journals Sequence learning recodes cortical representations instead of strengthening initial ones

2021 ◽  
Vol 17 (5) ◽  
pp. e1008969
Author(s):  
Kristjan Kalm ◽  
Dennis Norris
Keyword(s):  
Neural Activity ◽  
Sequence Learning ◽  
Visual Processing ◽  
Computational Models ◽  
Activity Patterns ◽  
Recall Task ◽  
Neural Representation ◽  
Processing Stream ◽  
Initial Sequence ◽  
Cortical Representations

We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patters from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations.

The “Mosaic Stage” in Amodal Completion as Characterized by Magnetoencephalography Responses

2006 ◽  
Vol 18 (8) ◽  
pp. 1394-1405 ◽  
Author(s):  
Gijs Plomp ◽  
Lichan Liu ◽  
Cees van Leeuwen ◽  
Andreas A. Ioannides
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Early Stage ◽  
Amodal Completion ◽  
Peak Latency ◽  
Per Se

We investigated the process of amodal completion in a same-different experiment in which test pairs were preceded by sequences of two figures. The first of these could be congruent to a global or local completion of an occluded part in the second figure, or a mosaic interpretation of it. We recorded and analyzed the magnetoencephalogram for the second figures. Compared to control conditions, in which unrelated primes were shown, occlusion and mosaic primes reduced the peak latency and amplitude of neural activity evoked by the occlusion patterns. Compared to occlusion primes, mosaic ones reduced the latency but increased the amplitude of evoked neural activity. Processes relating to a mosaic interpretation of the occlusion pattern, therefore, can dominate in an early stage of visual processing. The results did not provide evidence for the presence of a functional “mosaic stage” in completion per se, but characterize the mosaic interpretation as a qualitatively special one that can rapidly emerge in visual processing when context favors it.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals Recurrent circuitry is required to stabilize piriform cortex odor representations across brain states

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Kevin A Bolding ◽  
Shivathmihai Nagappan ◽  
Bao-Xia Han ◽  
Fan Wang ◽  
Kevin M Franks
Keyword(s):  
Neural Activity ◽  
Neural Circuits ◽  
Activity Patterns ◽  
Piriform Cortex ◽  
Theoretical Studies ◽  
Pattern Completion ◽  
Attractor Networks ◽  
Attractor Dynamics ◽  
Brain States ◽  
Associative Function

Pattern completion, or the ability to retrieve stable neural activity patterns from noisy or partial cues, is a fundamental feature of memory. Theoretical studies indicate that recurrently connected auto-associative or discrete attractor networks can perform this process. Although pattern completion and attractor dynamics have been observed in various recurrent neural circuits, the role recurrent circuitry plays in implementing these processes remains unclear. In recordings from head-fixed mice, we found that odor responses in olfactory bulb degrade under ketamine/xylazine anesthesia while responses immediately downstream, in piriform cortex, remain robust. Recurrent connections are required to stabilize cortical odor representations across states. Moreover, piriform odor representations exhibit attractor dynamics, both within and across trials, and these are also abolished when recurrent circuitry is eliminated. Here, we present converging evidence that recurrently-connected piriform populations stabilize sensory representations in response to degraded inputs, consistent with an auto-associative function for piriform cortex supported by recurrent circuitry.

scholarly journals Multiple states in ongoing neural activity in the rat visual cortex

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256791
Author(s):  
Daichi Konno ◽  
Shinji Nishimoto ◽  
Takafumi Suzuki ◽  
Yuji Ikegaya ◽  
Nobuyoshi Matsumoto
Keyword(s):  
Visual Cortex ◽  
Neural Activity ◽  
Activity Patterns ◽  
Electrode Array ◽  
Nonlinear Dimensionality Reduction ◽  
Neural Responses ◽  
Spontaneous Neural Activity ◽  
Custom Made ◽  
Visual Cortices ◽  
Freely Behaving

The brain continuously produces internal activity in the absence of afferently salient sensory input. Spontaneous neural activity is intrinsically defined by circuit structures and associated with the mode of information processing and behavioral responses. However, the spatiotemporal dynamics of spontaneous activity in the visual cortices of behaving animals remain almost elusive. Using a custom-made electrode array, we recorded 32-site electrocorticograms in the primary and secondary visual cortex of freely behaving rats and determined the propagation patterns of spontaneous neural activity. Nonlinear dimensionality reduction and unsupervised clustering revealed multiple discrete states of the activity patterns. The activity remained stable in one state and suddenly jumped to another state. The diversity and dynamics of the internally switching cortical states would imply flexibility of neural responses to various external inputs.

scholarly journals Distributed Subnetworks of Depression Defined by Direct Intracranial Neurophysiology

2020 ◽  
Author(s):  
KW Scangos ◽  
AN Khambhati ◽  
PM Daly ◽  
LW Owen ◽  
JR Manning ◽  
...  
Keyword(s):  
Neural Activity ◽  
Functional Organization ◽  
Activity Patterns ◽  
Computational Approach ◽  
Beta Activity ◽  
Targeted Intervention ◽  
Left Temporal Lobe ◽  
Spatiotemporal Resolution ◽  
Neural Recordings ◽  
Biological Substrates

AbstractQuantitative biological substrates of depression remain elusive. We carried out this study to determine whether application of a novel computational approach to high spatiotemporal resolution direct neural recordings may unlock the functional organization and coordinated activity patterns of depression networks. We identified two subnetworks conserved across the majority of individuals studied. The first was characterized by left temporal lobe hypoconnectivity and pathological beta activity. The second was characterized by a hypoactive, but hyperconnected left frontal cortex. These findings identify distributed circuit activity associated with depression, link neural activity with functional connectivity profiles, and inform strategies for personalized targeted intervention.

scholarly journals Olfaction Modulates Early Neural Responses to Matching Visual Objects

2015 ◽  
Vol 27 (4) ◽  
pp. 832-841 ◽  
Author(s):  
Amanda K. Robinson ◽  
Judith Reinhard ◽  
Jason B. Mattingley
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Sensory Information ◽  
Neural Correlates ◽  
Neural Responses ◽  
Visual Objects ◽  
Cortical Areas ◽  
Early Visual Processing ◽  
Considerable Research ◽  
Matter Concentration

Sensory information is initially registered within anatomically and functionally segregated brain networks but is also integrated across modalities in higher cortical areas. Although considerable research has focused on uncovering the neural correlates of multisensory integration for the modalities of vision, audition, and touch, much less attention has been devoted to understanding interactions between vision and olfaction in humans. In this study, we asked how odors affect neural activity evoked by images of familiar visual objects associated with characteristic smells. We employed scalp-recorded EEG to measure visual ERPs evoked by briefly presented pictures of familiar objects, such as an orange, mint leaves, or a rose. During presentation of each visual stimulus, participants inhaled either a matching odor, a nonmatching odor, or plain air. The N1 component of the visual ERP was significantly enhanced for matching odors in women, but not in men. This is consistent with evidence that women are superior in detecting, discriminating, and identifying odors and that they have a higher gray matter concentration in olfactory areas of the OFC. We conclude that early visual processing is influenced by olfactory cues because of associations between odors and the objects that emit them, and that these associations are stronger in women than in men.

scholarly journals Exploring the role of expectations and stimulus relevance on stimulus-specific neural representations and conscious report

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Erik L Meijs ◽  
Pim Mostert ◽  
Heleen A Slagter ◽  
Floris P de Lange ◽  
Simon van Gaal
Keyword(s):  
Attentional Blink ◽  
Neural Activity ◽  
Subjective Experience ◽  
Activity Patterns ◽  
Neural Mechanisms ◽  
Top Down ◽  
Neural Representations ◽  
Dependent Signal ◽  
Task Irrelevant

Abstract Subjective experience can be influenced by top-down factors, such as expectations and stimulus relevance. Recently, it has been shown that expectations can enhance the likelihood that a stimulus is consciously reported, but the neural mechanisms supporting this enhancement are still unclear. We manipulated stimulus expectations within the attentional blink (AB) paradigm using letters and combined visual psychophysics with magnetoencephalographic (MEG) recordings to investigate whether prior expectations may enhance conscious access by sharpening stimulus-specific neural representations. We further explored how stimulus-specific neural activity patterns are affected by the factors expectation, stimulus relevance and conscious report. First, we show that valid expectations about the identity of an upcoming stimulus increase the likelihood that it is consciously reported. Second, using a series of multivariate decoding analyses, we show that the identity of letters presented in and out of the AB can be reliably decoded from MEG data. Third, we show that early sensory stimulus-specific neural representations are similar for reported and missed target letters in the AB task (active report required) and an oddball task in which the letter was clearly presented but its identity was task-irrelevant. However, later sustained and stable stimulus-specific representations were uniquely observed when target letters were consciously reported (decision-dependent signal). Fourth, we show that global pre-stimulus neural activity biased perceptual decisions for a ‘seen’ response. Fifth and last, no evidence was obtained for the sharpening of sensory representations by top-down expectations. We discuss these findings in light of emerging models of perception and conscious report highlighting the role of expectations and stimulus relevance.

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