Tweaking synapses
Nature Reviews Neuroscience, Published online: 28 September 2020;
doi:10.1038/s41583-020-00389-6
Strengthening of the developing retinogeniculate circuit in mouse pups is
promoted by a neuronal receptor and locally restricted by the microglial
release of the receptor’s ligand.
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Nature Reviews Neuroscience, Published online: 28 September 2020;
doi:10.1038/s41583-020-00389-6
Strengthening of the developing retinogeniculate circuit in mouse pups is
promoted by a neuronal receptor and locally restricted by the microglial
release of the receptor’s ligand.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Nature Reviews Neuroscience
Tweaking synapses
Strengthening of the developing retinogeniculate circuit in mouse pups is promoted by a neuronal receptor and locally restricted by the microglial release of the receptor’s ligand.
https://twitter.com/oritpeleg/status/1312074215571419137?s=20
APS March meeting is happening online this year (March 15-19), and we have a Focus Session alert!
Physics of Social Interactions: Work on interactions between organisms or on inanimate interactions that mimic social ones
Organized by @oritpeleg &
@greg_stephens
Please RT!
#events
Follow: @theTuringMachine
APS March meeting is happening online this year (March 15-19), and we have a Focus Session alert!
Physics of Social Interactions: Work on interactions between organisms or on inanimate interactions that mimic social ones
Organized by @oritpeleg &
@greg_stephens
Please RT!
#events
Follow: @theTuringMachine
Open science: Sharing is caring, but is privacy theft? by David Mehler and Kevin Weiner
Open Science (OS) is a movement toward increased sharing among scientists of
their data, their materials, their computer code, their papers, and their peer
reviews. The ultimate goal of this movement is to boost collaborative
Read More: [ Link ]
#articles
Follow: @theTuringMachine
Open Science (OS) is a movement toward increased sharing among scientists of
their data, their materials, their computer code, their papers, and their peer
reviews. The ultimate goal of this movement is to boost collaborative
Read More: [ Link ]
#articles
Follow: @theTuringMachine
The Official PLOS Blog
The Official PLOS Blog - The Official PLOS Blog covers PLOS initiatives that address our core principles.
CALL FOR PAPERS
Reinforcement learning (RL) algorithms learn through rewards and a process of trial-and-error. This approach is strongly inspired by the study of animal behaviour and has led to outstanding achievements.
Link: Google Site
#events
Follow: @theTuringMachine
Reinforcement learning (RL) algorithms learn through rewards and a process of trial-and-error. This approach is strongly inspired by the study of animal behaviour and has led to outstanding achievements.
Link: Google Site
#events
Follow: @theTuringMachine
https://www.probabilisticworld.com/frequentist-bayesian-approaches-inferential-statistics/
#spare_time
#spare_time
Probabilistic World
Frequentist and Bayesian Approaches in Statistics
What is statistics about? Well, imagine you obtained some data from a particular collection of things. It could be the heights of individuals within a group of people, the weights of cats in a clowder, the number of petals in a bouquet of flowers, and so…
Mapping gut neurons
Nature Reviews Neuroscience, Published online: 24 September 2020;
doi:10.1038/s41583-020-00386-9
Mapping gut neurons
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Nature Reviews Neuroscience, Published online: 24 September 2020;
doi:10.1038/s41583-020-00386-9
Mapping gut neurons
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Nature Reviews Neuroscience
Mapping gut neurons
GENE EXPRESSION
Fractional infinite-horizon optimal control problems with a feed forward neural network scheme
Volume 30, Issue 1-4, February - November 2019, Page 125-147
.
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Volume 30, Issue 1-4, February - November 2019, Page 125-147
.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Taylor & Francis
Fractional infinite-horizon optimal control problems with a feed forward neural network scheme
(2019). Fractional infinite-horizon optimal control problems with a feed forward neural network scheme. Network: Computation in Neural Systems: Vol. 30, No. 1-4, pp. 125-147.
Alternative continuous- and discrete-time neural networks for image restoration
Volume 30, Issue 1-4, February - November 2019, Page 107-124
.
Read More: [ Source ]
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Follow: @theTuringMachine
Volume 30, Issue 1-4, February - November 2019, Page 107-124
.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Taylor & Francis
Alternative continuous- and discrete-time neural networks for image restoration
(2019). Alternative continuous- and discrete-time neural networks for image restoration. Network: Computation in Neural Systems: Vol. 30, No. 1-4, pp. 107-124.
Retrospective Evaluation of Sequential Events and the Influence of Preference-Dependent Working Memory: A Computational Examination
Humans organize sequences of events into a single overall experience, and
evaluate the aggregated experience as a whole, such as a generally pleasant
dinner, movie, or trip. However, such evaluations are potentially
computationally taxing, and so our brains must employ heuristics (i.e.,
approximations). For example, the peak-end rule hypothesis suggests that we
average the peaks and end of a sequential event vs. integrating every moment.
However, there is no general model to test viable hypotheses quantitatively.
Here, we propose a general model and test among multiple specific ones, while
also examining the role of working memory. The models were tested with a novel
picture-rating task. We first compared averaging across entire sequences vs.
the peak-end heuristic. Correlation tests indicated that averaging prevailed,
with peak and end both still having significant prediction power. Given this,
we developed generalized order-dependent and relative-preference-dependent
models to subsume averaging, peak and end. The combined model improved the
prediction power. However, based on limitations of relative-
preference—including imposing a potentially arbitrary ranking among
preferences—we introduced an absolute-preference-dependent model, which
successfully explained the remembered utilities. Yet, because using all
experiences in a sequence requires too much memory as real-world settings
scale, we then tested “windowed” models, i.e., evaluation within a specified
window. The windowed (absolute) preference-dependent (WP) model explained the
empirical data with long sequences better than without windowing. However,
because fixed-windowed models harbor their own limitations—including an
inability to capture peak-event influences beyond a fixed window—we then
developed discounting models. With (absolute) preference-dependence added to
the discounting rate, the results showed that the discounting model reflected
the actual working memory of the participants, and that the preference-
dependent discounting (PD) model described different features from the WP
model. Taken together, we propose a combined WP-PD model as a means by which
people evaluate experiences, suggesting preference-dependent working-memory as
a significant factor underlying our evaluations.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Humans organize sequences of events into a single overall experience, and
evaluate the aggregated experience as a whole, such as a generally pleasant
dinner, movie, or trip. However, such evaluations are potentially
computationally taxing, and so our brains must employ heuristics (i.e.,
approximations). For example, the peak-end rule hypothesis suggests that we
average the peaks and end of a sequential event vs. integrating every moment.
However, there is no general model to test viable hypotheses quantitatively.
Here, we propose a general model and test among multiple specific ones, while
also examining the role of working memory. The models were tested with a novel
picture-rating task. We first compared averaging across entire sequences vs.
the peak-end heuristic. Correlation tests indicated that averaging prevailed,
with peak and end both still having significant prediction power. Given this,
we developed generalized order-dependent and relative-preference-dependent
models to subsume averaging, peak and end. The combined model improved the
prediction power. However, based on limitations of relative-
preference—including imposing a potentially arbitrary ranking among
preferences—we introduced an absolute-preference-dependent model, which
successfully explained the remembered utilities. Yet, because using all
experiences in a sequence requires too much memory as real-world settings
scale, we then tested “windowed” models, i.e., evaluation within a specified
window. The windowed (absolute) preference-dependent (WP) model explained the
empirical data with long sequences better than without windowing. However,
because fixed-windowed models harbor their own limitations—including an
inability to capture peak-event influences beyond a fixed window—we then
developed discounting models. With (absolute) preference-dependence added to
the discounting rate, the results showed that the discounting model reflected
the actual working memory of the participants, and that the preference-
dependent discounting (PD) model described different features from the WP
model. Taken together, we propose a combined WP-PD model as a means by which
people evaluate experiences, suggesting preference-dependent working-memory as
a significant factor underlying our evaluations.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Frontiers
Retrospective Evaluation of Sequential Events and the Influence of Preference-Dependent Working Memory: A Computational Examination
Humans organize sequences of events into a single overall experience, and evaluate the aggregated experience as a whole, such as a generally pleasant dinner, movie, or trip. However, such evaluations are potentially computationally taxing, and so our brains…
A Computational Model of the Cholinergic Modulation of CA1 Pyramidal Cell Activity
Dysfunction in cholinergic modulation has been linked to a variety of
cognitive disorders including Alzheimer's disease. The important role of this
neurotransmitter has been explored in a variety of experiments, yet many
questions remain unanswered about the contribution of cholinergic modulation
to healthy hippocampal function. To address this question, we have developed a
model of CA1 pyramidal neuron that takes into consideration muscarinic
receptor activation in response to changes in extracellular concentration of
acetylcholine and its effects on cellular excitability and downstream
intracellular calcium dynamics. This model incorporates a variety of molecular
agents to accurately simulate several processes heretofore ignored in
computational modeling of CA1 pyramidal neurons. These processes include the
inhibition of ionic channels by phospholipid depletion along with the release
of calcium from intracellular stores (i.e., the endoplasmic reticulum). This
paper describes the model and the methods used to calibrate its behavior to
match experimental results. The result of this work is a compartmental model
with calibrated mechanisms for simulating the intracellular calcium dynamics
of CA1 pyramidal cells with a focus on those related to release from calcium
stores in the endoplasmic reticulum. From this model we also make various
predictions for how the inhibitory and excitatory responses to cholinergic
modulation vary with agonist concentration. This model expands the
capabilities of CA1 pyramidal cell models through the explicit modeling of
molecular interactions involved in healthy cognitive function and disease.
Through this expanded model we come closer to simulating these diseases and
gaining the knowledge required to develop novel treatments.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Dysfunction in cholinergic modulation has been linked to a variety of
cognitive disorders including Alzheimer's disease. The important role of this
neurotransmitter has been explored in a variety of experiments, yet many
questions remain unanswered about the contribution of cholinergic modulation
to healthy hippocampal function. To address this question, we have developed a
model of CA1 pyramidal neuron that takes into consideration muscarinic
receptor activation in response to changes in extracellular concentration of
acetylcholine and its effects on cellular excitability and downstream
intracellular calcium dynamics. This model incorporates a variety of molecular
agents to accurately simulate several processes heretofore ignored in
computational modeling of CA1 pyramidal neurons. These processes include the
inhibition of ionic channels by phospholipid depletion along with the release
of calcium from intracellular stores (i.e., the endoplasmic reticulum). This
paper describes the model and the methods used to calibrate its behavior to
match experimental results. The result of this work is a compartmental model
with calibrated mechanisms for simulating the intracellular calcium dynamics
of CA1 pyramidal cells with a focus on those related to release from calcium
stores in the endoplasmic reticulum. From this model we also make various
predictions for how the inhibitory and excitatory responses to cholinergic
modulation vary with agonist concentration. This model expands the
capabilities of CA1 pyramidal cell models through the explicit modeling of
molecular interactions involved in healthy cognitive function and disease.
Through this expanded model we come closer to simulating these diseases and
gaining the knowledge required to develop novel treatments.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Frontiers
A Computational Model of the Cholinergic Modulation of CA1 Pyramidal Cell Activity
Dysfunction in cholinergic modulation has been linked to a variety of cognitive disorders including Alzheimer's disease. The important role of this neurotransmitter has been explored in a variety of experiments, yet many questions remain unanswered about…
High-fidelity vibrokinetic stimulation induces sustained changes in intercortical coherence during a
cinematic experience
Objective. High-fidelity vibrokinetic (HFVK) technology is widely used to
enhance the immersiveness of audiovisual (AV) entertainment experiences.
However, despite evidence that HFVK technology does subjectively enhance AV
immersion, the underlying mechanism has not been clarified. Neurophysiological
studies could provide important evidence to illuminate this mechanism, thereby
benefiting HFVK stimulus design, and facilitating expansion of HFVK
technology. Approach. We conducted a between-subjects (VK, N = 11; Control, N
= 9) exploratory study to measure the effect of HFVK stimulation through an
HFVK seat on electroencephalographic cortical activity during an AV cinematic
experience. Subjective appreciation of the experience was assessed and
incorporated into statistical models exploring the effects of HFVK stimulation
across cortical brain areas. We separately analyzed alpha-band (8–12 Hz) and
theta-band (5–7 Hz) activities as indices of engagement ...
Read More: [ Source ]
#articles
Follow: @theTuringMachine
cinematic experience
Objective. High-fidelity vibrokinetic (HFVK) technology is widely used to
enhance the immersiveness of audiovisual (AV) entertainment experiences.
However, despite evidence that HFVK technology does subjectively enhance AV
immersion, the underlying mechanism has not been clarified. Neurophysiological
studies could provide important evidence to illuminate this mechanism, thereby
benefiting HFVK stimulus design, and facilitating expansion of HFVK
technology. Approach. We conducted a between-subjects (VK, N = 11; Control, N
= 9) exploratory study to measure the effect of HFVK stimulation through an
HFVK seat on electroencephalographic cortical activity during an AV cinematic
experience. Subjective appreciation of the experience was assessed and
incorporated into statistical models exploring the effects of HFVK stimulation
across cortical brain areas. We separately analyzed alpha-band (8–12 Hz) and
theta-band (5–7 Hz) activities as indices of engagement ...
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Mindful brains, By Emma Twait and Tzipi Horowitz-Kraus
In the world with so much buzz around us, it can be difficult to unplug from
work and not think about the never-ending list of things to do. Stress
accumulates…. If you can relate to
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#articles
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In the world with so much buzz around us, it can be difficult to unplug from
work and not think about the never-ending list of things to do. Stress
accumulates…. If you can relate to
Read More: [ Source ]
#articles
Follow: @theTuringMachine
The Official PLOS Blog
The Official PLOS Blog - The Official PLOS Blog covers PLOS initiatives that address our core principles.
GEM 2021
Feb 16 - 18 2021
Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology....
Find out more: [ link ]
#events
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Feb 16 - 18 2021
Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology....
Find out more: [ link ]
#events
Follow: @theTuringMachine
Neural Stem Cells Direct Axon Guidance via Their Radial Fiber Scaffold
Kaur et al. show that the radial glial scaffold of neural stem cells from
medial ganglionic eminence directs corticospinal and other axons through a
previously unknown choice point at the striatopallidal junction in an
RND3/ARHGAP35-dependent manner. Within corticospinal neurons, FEZF2-dependent
Rnd3 expression regulates dendritic spinogenesis, axon elongation, and pontine
midline crossing.
Read More: [ Source ]
#articles
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Kaur et al. show that the radial glial scaffold of neural stem cells from
medial ganglionic eminence directs corticospinal and other axons through a
previously unknown choice point at the striatopallidal junction in an
RND3/ARHGAP35-dependent manner. Within corticospinal neurons, FEZF2-dependent
Rnd3 expression regulates dendritic spinogenesis, axon elongation, and pontine
midline crossing.
Read More: [ Source ]
#articles
Follow: @theTuringMachine
Enhancing gesture decoding performance using signals from posterior parietal cortex: a
stereo-electroencephalograhy (SEEG) study
Objective . Hand movement is a crucial function for humans’ daily life.
Developing brain-machine interface (BMI) to control a robotic hand by brain
signals would help the severely paralyzed people partially regain the
functional independence. Previous intracranial electroencephalography
(iEEG)-based BMIs towards gesture decoding mostly used neural signals from the
primary sensorimotor cortex while ignoring the hand movement related signals
from posterior parietal cortex (PPC). Here, we propose combining iEEG
recordings from PPC with that from primary sensorimotor cortex to enhance the
gesture decoding performance of iEEG-based BMI. Approach .
Stereoelectroencephalography (SEEG) signals from 25 epilepsy subjects were
recorded when they performed a three-class hand gesture task. Across all 25
subjects, we identified 524, 114 and 221 electrodes from three regions of
interest (ROIs), including PPC, postcentral cortex (POC) and precentral cortex
(PRC), respectively. Base...
Read More: [ Source ]
#articles
Follow: @theTuringMachine
stereo-electroencephalograhy (SEEG) study
Objective . Hand movement is a crucial function for humans’ daily life.
Developing brain-machine interface (BMI) to control a robotic hand by brain
signals would help the severely paralyzed people partially regain the
functional independence. Previous intracranial electroencephalography
(iEEG)-based BMIs towards gesture decoding mostly used neural signals from the
primary sensorimotor cortex while ignoring the hand movement related signals
from posterior parietal cortex (PPC). Here, we propose combining iEEG
recordings from PPC with that from primary sensorimotor cortex to enhance the
gesture decoding performance of iEEG-based BMI. Approach .
Stereoelectroencephalography (SEEG) signals from 25 epilepsy subjects were
recorded when they performed a three-class hand gesture task. Across all 25
subjects, we identified 524, 114 and 221 electrodes from three regions of
interest (ROIs), including PPC, postcentral cortex (POC) and precentral cortex
(PRC), respectively. Base...
Read More: [ Source ]
#articles
Follow: @theTuringMachine
The relationship between morphological properties and thresholds to extracellular electric
stimulation in α RGCs
Objective . Retinal prostheses strive to restore vison to patients that are
blind from retinal degeneration by electrically stimulating surviving retinal
ganglion cells (RGCs). The quality of elicited percepts remains limited
however and it is desirable to develop improved stimulation strategies. Here,
we examine how the anatomical and biophysical properties of RGCs influence
activation thresholds, including the effects of variations found naturally.
Approach . Detailed reconstructions were made of a large number of mouse α
RGCs and were used to create an array of model cells; the models were used to
study the effects of individual anatomical features on activation threshold to
electric stimulation. Stimulation was delivered epiretinally from a point-
source or disk electrode and consisted of monophasic or biphasic rectangular
pulses. Main results. Modeling results show that the region of minimum
threshold always is within the axon initial segment (AIS)...
Read More: [ Source ]
#articles
Follow: @theTuringMachine
stimulation in α RGCs
Objective . Retinal prostheses strive to restore vison to patients that are
blind from retinal degeneration by electrically stimulating surviving retinal
ganglion cells (RGCs). The quality of elicited percepts remains limited
however and it is desirable to develop improved stimulation strategies. Here,
we examine how the anatomical and biophysical properties of RGCs influence
activation thresholds, including the effects of variations found naturally.
Approach . Detailed reconstructions were made of a large number of mouse α
RGCs and were used to create an array of model cells; the models were used to
study the effects of individual anatomical features on activation threshold to
electric stimulation. Stimulation was delivered epiretinally from a point-
source or disk electrode and consisted of monophasic or biphasic rectangular
pulses. Main results. Modeling results show that the region of minimum
threshold always is within the axon initial segment (AIS)...
Read More: [ Source ]
#articles
Follow: @theTuringMachine