Synesthetic Binding and the Reactivation Model of Memory

2017 ◽  
Author(s):  
Berit Brogaard
Keyword(s):  
Sensory Neurons ◽  
Memory Retrieval ◽  
Brain Activity ◽  
Receptive Fields ◽  
Memory Model ◽  
Multisensory Perception ◽  
Feedback Mechanisms

Despite the recent surge in research on, and interest in, synesthesia, the mechanism underlying this condition is still unknown. Feedforward mechanisms involving overlapping receptive fields of sensory neurons as well as feedback mechanisms involving a lack of signal disinhibition have been proposed. Here I show that a broad range of studies of developmental synesthesia indicate that the mechanism underlying the phenomenon may in some cases involve the reinstatement of brain activity in sensory or cognitive streams in a way that is similar to what happens during memory retrieval of semantically associated items. In the chapter’s final sections I look at the relevance of synesthesia research, given the memory model, to our understanding of multisensory perception and common mapping patterns.

scholarly journals Age differences in brain activity related to unsuccessful declarative memory retrieval

2015 ◽  
Vol 1612 ◽  
pp. 30-47 ◽  
Author(s):  
Cheryl L. Grady ◽  
Marie St-Laurent ◽  
Hana Burianová
Keyword(s):  
Age Differences ◽  
Memory Retrieval ◽  
Declarative Memory ◽  
Brain Activity

Frontal Brain Activity during Episodic and Semantic Retrieval: Insights from Event-Related Potentials

1999 ◽  
Vol 11 (6) ◽  
pp. 598-609 ◽  
Author(s):  
Charan Ranganath ◽  
Ken A. Paller
Keyword(s):  
Prefrontal Cortex ◽  
Memory Retrieval ◽  
Brain Activity ◽  
Novelty Detection ◽  
Event Related Potentials ◽  
Episodic Retrieval ◽  
Semantic Retrieval ◽  
Retrieval Task ◽  
Related Potentials ◽  
The Right

Previous neuropsychological and neuroimaging results have implicated the prefrontal cortex in memory retrieval, although its precise role is unclear. In the present study, we examined patterns of brain electrical activity during retrieval of episodic and semantic memories. In the episodic retrieval task, participants retrieved autobiographical memories in response to event cues. In the semantic retrieval task, participants generated exemplars in response to category cues. Novel sounds presented intermittently during memory retrieval elicited a series of brain potentials including one identifiable as the P3a potential. Based on prior research linking P3a with novelty detection and with the frontal lobes, we predicted that P3a would be reduced to the extent that novelty detection and memory retrieval interfere with each other. Results during episodic and semantic retrieval tasks were compared to results during a task in which subjects attended to the auditory stimuli. P3a amplitudes were reduced during episodic retrieval, particularly at right lateral frontal scalp locations. A similar but less lateralized pattern of frontal P3a reduction was observed during semantic retrieval. These findings support the notion that the right prefrontal cortex is engaged in the service of memory retrieval, particularly for episodic memories.

scholarly journals Neural theta oscillations support semantic memory retrieval

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Martin Marko ◽  
Barbora Cimrová ◽  
Igor Riečanský
Keyword(s):  
Memory Retrieval ◽  
Relative Phase ◽  
Brain Activity ◽  
Theta Oscillations ◽  
Semantic Retrieval ◽  
Theta Band ◽  
Retrieval Performance ◽  
Automatic Retrieval ◽  
Transcranial Alternating Current Stimulation ◽  
Oscillatory Brain Activity

AbstractLexical–semantic retrieval emerges through the interactions of distributed prefrontal and perisylvian brain networks. Growing evidence suggests that synchronous theta band neural oscillations might play a role in this process, yet, their functional significance remains elusive. Here, we used transcranial alternating current stimulation to induce exogenous theta oscillations at 6 Hz (θ-tACS) over left prefrontal and posterior perisylvian cortex with a 180° (anti-phase) and 0° (in-phase) relative phase difference while participants performed automatic and controlled retrieval tasks. We demonstrate that θ-tACS significantly modulated the retrieval performance and its effects were both task- and phase-specific: the in-phase tACS impaired controlled retrieval, whereas the anti-phase tACS improved controlled but impaired automatic retrieval. These findings indicate that theta band oscillatory brain activity supports binding of semantically related representations via a phase-dependent modulation of semantic activation or maintenance.

Leech Mechanosensation

2017 ◽  
Author(s):  
Brian D. Burrell
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Sensory Neurons ◽  
Receptive Fields ◽  
Model Systems ◽  
Sensory Cells ◽  
Mechanical Stimuli ◽  
Nociceptive Neurons ◽  
Mechanosensory Neurons ◽  
The Central Nervous System

The medicinal leech (Hirudo verbana) is an annelid (segmented worm) and one of the classic model systems in neuroscience. It has been used in research for over 50 years and was one of the first animals in which intracellular recordings of mechanosensory neurons were carried out. Remarkably, the leech has three main classes of mechanosensory neurons that exhibit many of the same properties found in vertebrates. The most sensitive of these neurons are the touch cells, which are rapidly adapting neurons that detect low-intensity mechanical stimuli. Next are the pressure cells, which are slow-adapting sensory neurons that respond to higher intensity, sustained mechanostimulation. Finally, there are nociceptive neurons, which have the highest threshold and respond to potentially damaging mechanostimuli, such as a pinch. As observed in mammals, the leech has separate mechanosensitive and polymodal nociceptors, the latter responding to mechanical, thermal, and chemical stimuli. The cell bodies for all three types of mechanosensitive neurons are found in the central nervous system where they are arranged as bilateral pairs. Each neuron extends processes to the skin where they form discrete receptive fields. In the touch and pressure cells, these receptive fields are arranged along the dorsal-ventral axis. For the mechano-only and polymodal nociceptive neurons, the peripheral receptive fields overlap with the mechano-only nociceptor, which also innervates the gut. The leech also has a type of mechanosensitive cell located in the periphery that responds to vibrations in the water and is used, in part, to detect potential prey nearby. In the central nervous system, the touch, pressure, and nociceptive cells all form synaptic connections with a variety of motor neurons, interneurons, and even each other, using glutamate as the neurotransmitter. Synaptic transmission by these cells can be modulated by a variety of activity-dependent processes as well as the influence of neuromodulatory transmitters, such as serotonin. The output of these sensory neurons can also be modulated by conduction block, a process in which action potentials fail to propagate to all the synaptic release sites, decreasing synaptic output. Activity in these sensory neurons leads to the initiation of a number of different motor behaviors involved in locomotion, such as swimming and crawling, as well as behaviors designed to recoil from aversive/noxious stimuli, such as local bending and shortening. In the case of local bending, the leech is able to bend in the appropriate direction away from the offending stimuli. It does so through a combination of which mechanosensory cell receptive fields have been activated and the relative activation of multiple sensory cells decoded by a layer of downstream interneurons.

scholarly journals Reactivation of encoding-related brain activity during memory retrieval

2000 ◽  
Vol 97 (20) ◽  
pp. 11120-11124 ◽  
Author(s):  
L. Nyberg ◽  
R. Habib ◽  
A. R. McIntosh ◽  
E. Tulving
Keyword(s):  
Memory Retrieval ◽  
Brain Activity

scholarly journals The feature-weighted receptive field: an interpretable encoding model for complex feature spaces

2017 ◽  
Author(s):  
Ghislain St-Yves ◽  
Thomas Naselaris
Keyword(s):  
Receptive Field ◽  
Frequency Tuning ◽  
Brain Activity ◽  
Receptive Fields ◽  
Visual Space ◽  
Model Complexity ◽  
Visual Features ◽  
Natural Scenes ◽  
Feature Maps ◽  
Feature Map

AbstractWe introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map—a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: “where” parameters that characterize the location and extent of pooling over visual features, and “what” parameters that characterize tuning to visual features. The “where” parameters are analogous to classical receptive fields, while “what” parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation.We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model’s application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity.

scholarly journals Synergistic positive feedback underlying seizure initiation

2021 ◽  
Author(s):  
Rob T. Graham ◽  
R. Ryley Parrish ◽  
Laura Alberio ◽  
Emily L. Johnson ◽  
Laura J. Owens ◽  
...  
Keyword(s):  
Positive Feedback ◽  
State Transition ◽  
Seizure Activity ◽  
Brain Activity ◽  
Epileptic Activity ◽  
Brain State ◽  
Seizure Onset ◽  
Feedback Mechanisms ◽  
Optogenetic Stimulation ◽  
Stimulation Paradigm

Seizure onset is a critically important brain state transition that has proved very difficult to predict accurately from recordings of brain activity. Here we show that an intermittent optogenetic stimulation paradigm reveals a latent change in dendritic excitability that is tightly correlated to the onset of seizure activity. Our data show how the precipitous nature of the transition can be understood in terms of multiple, synergistic positive feedback mechanisms: raised intracellular Cl- and extracellular K+, coupled to a reduced threshold for dendritic plateau potentials, and which in turn leads to a switch to pyramidal burst firing. Notably, the stimulation paradigm also delays the evolving epileptic activity, meaning that not only can one monitor seizure risk safely, but it may also even have an additional anti-epileptic benefit.

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