neuro

Neural criticality from effective latent variables. (arXiv:2301.00759v3 [q-bio.NC] UPDATED)

2023-10-16T12:36:23+00:00

Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is "avalanche criticality," which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.

Sequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule

2023-08-21T00:00:00+00:00

Detecting Hidden Brain States With Mathematical Models

2023-03-14T20:18:45+00:00

Using a mathematical model to study how the brain predicts information and learns, researchers discovered signals for accuracy are found in the anterior insula and anxiety affects activity levels in this brain region.

Our Memory for Objects Might Be Better Than We Think

2023-01-23T18:58:59+00:00

A test of temporal and spatial memory reveals people are better at remembering where and when people saw objects than previously thought.

How the Brain Stores Remote Fear Memory

2022-12-23T20:14:28+00:00

Remote fear memories, or memories of trauma formed in the distant past, are stored in the connections between neurons in the prefrontal cortex.

Scientists Capture Detailed Snapshots of Mouse Brain Cells Nibbling on Neurons

2022-11-28T22:52:32+00:00

Oligodendrocyte precursor cells (OPCs) play a significant role in synaptic pruning, a new study reveals.

Unique Features of Octopus Create an Entirely New Way of Designing a Nervous System

2022-11-28T21:39:29+00:00

Researchers discovered a structure within the octopus nervous system by which the intramuscular nerve cords, which help the cephalopod to sense its arm movements, connect arms on the opposite side of the animal.

Human brain cells in a dish learn to play Pong in real time -- ScienceDaily

2022-10-13T01:52:24+00:00

Human and mouse neurons in a dish learned to play the video game Pong, researchers report. The experiments are evidence that even brain cells in a dish can exhibit inherent intelligence, modifying their behavior over time.

Neuroscience data analysis in the cloud

2022-09-06T00:00:00+00:00

Scientists Break the Direction of Time Down to the Cellular Level in Mind-Bending Study

2022-09-01T02:42:19+00:00

The passage of time is a universal facet of life. But what is time, and why do we experience it as something that has direction, with a past and a future? In a new study, scientists have broken down this "arrow of time" to a microscopic physical level.

Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures

2022-07-10T14:51:23+00:00

Time is of the essence in how neural codes, synchronies, and oscillations might function in encoding, representation, transmission, integration, storage, and retrieval of information in brains. This Hypothesis and Theory article examines observed and possible relations between codes, synchronies, oscillations, and types of neural networks they require. Toward reverse-engineering informational functions in brains, prospective, alternative neural architectures incorporating principles from radio modulation and demodulation, active reverberant circuits, distributed content-addressable memory, signal-signal time-domain correlation and convolution operations, spike-correlation-based holography, and self-organizing, autoencoding anticipatory systems are outlined. Synchronies and oscillations are thought to subserve many possible functions: sensation, perception, action, cognition, motivation, affect, memory, attention, anticipation, and imagination. These include direct involvement in coding attributes of events and objects through phase-locking as well as characteristic patterns of spike latency and oscillatory response. They are thought to be involved in segmentation and binding, working memory, attention, gating and routing of signals, temporal reset mechanisms, inter-regional coordination, time discretization, time-warping transformations, and support for temporal wave-interference based operations. A high level, partial taxonomy of neural codes consists of channel, temporal pattern, and spike latency codes. The functional roles of synchronies and oscillations in candidate neural codes, including oscillatory phase-offset codes, are outlined. Various forms of multiplexing neural signals are considered: time-division, frequency-division, code-division, oscillatory-phase, synchronized channels, oscillatory hierarchies, polychronous ensembles. An expandable, annotative neural spike train framework for encoding low- and high-level attributes of events and objects is proposed. Coding schemes require appropriate neural architectures for their interpretation. Time-delay, oscillatory, wave-interference, synfire chain, polychronous, and neural timing networks are discussed. Some novel concepts for formulating an alternative, more time-centric theory of brain function are discussed. As in radio communication systems, brains can be regarded as networks of dynamic, adaptive transceivers that broadcast and selectively receive multiplexed temporally-patterned pulse signals. These signals enable complex signal interactions that select, reinforce, and bind common subpatterns and create emergent lower dimensional signals that propagate through spreading activation interference networks. If memory traces share the same kind of temporal pattern forms as do active neuronal representations, then distributed, holograph-like content-addressable memories are made possible via temporal pattern resonances.

Emergent organization of receptive fields in networks of excitatory and inhibitory neurons. (arXiv:2205.13614v1 [q-bio.NC])

2022-05-30T12:37:51+00:00

Local patterns of excitation and inhibition that can generate neural waves are studied as a computational mechanism underlying the organization of neuronal tunings. Sparse coding algorithms based on networks of excitatory and inhibitory neurons are proposed that exhibit topographic maps as the receptive fields are adapted to input stimuli. Motivated by a leaky integrate-and-fire model of neural waves, we propose an activation model that is more typical of artificial neural networks. Computational experiments with the activation model using both natural images and natural language text are presented. In the case of images, familiar "pinwheel" patterns of oriented edge detectors emerge; in the case of text, the resulting topographic maps exhibit a 2-dimensional representation of granular word semantics. Experiments with a synthetic model of somatosensory input are used to investigate how the network dynamics may affect plasticity of neuronal maps under changes to the inputs.

Deep Residual Convolutional Neural Networks for Brain–Computer Interface to Visualize Neural Processing of Hand Movements in the Human Brain

2022-05-21T05:27:36+00:00

Concomitant with the development of deep learning, brain–computer interface (BCI) decoding technology has been rapidly evolving. Convolutional neural networks (CNNs), which are generally used as electroencephalography (EEG) classification models, are often deployed in BCI prototypes to improve the estimation accuracy of a participant's brain activity. However, because most BCI models are trained, validated, and tested within-subject cross-validation and there is no corresponding generalization model, their applicability to unknown participants is not guaranteed. In this study, to facilitate the generalization of BCI model performance to unknown participants, we trained a model comprising multiple layers of residual CNNs and visualized the reasons for BCI classification to reveal the location and timing of neural activities that contribute to classification. Specifically, to develop a BCI that can distinguish between rest, left-hand movement, and right-hand movement tasks with high accuracy, we created multilayers of CNNs, inserted residual networks into the multilayers, and used a larger dataset than in previous studies. The constructed model was analyzed with gradient-class activation mapping (Grad-CAM). We evaluated the developed model subject cross-validation and found that it achieved significantly improved accuracy (85.69 ± 1.10%) compared with conventional models or without residual networks. Grad-CAM analysis of the classification of cases in which our model produced correct answers showed localized activity near the premotor cortex. These results confirm the effectiveness of inserting residual networks into CNNs for tuning BCI. Further, they suggest that recording EEG signals over the premotor cortex and some other areas contributes to high classification accuracy.

Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines. (arXiv:2205.06313v1 [q-bio.MN])

2022-05-16T12:38:42+00:00

Can a micron sized sack of interacting molecules understand, and adapt to a constantly-fluctuating environment? Cellular life provides an existence proof in the affirmative, but the principles that allow for life's existence are far from being proven. One challenge in engineering and understanding biochemical computation is the intrinsic noise due to chemical fluctuations. In this paper, we draw insights from machine learning theory, chemical reaction network theory, and statistical physics to show that the broad and biologically relevant class of detailed balanced chemical reaction networks is capable of representing and conditioning complex distributions. These results illustrate how a biochemical computer can use intrinsic chemical noise to perform complex computations. Furthermore, we use our explicit physical model to derive thermodynamic costs of inference.

Efficient dendritic learning as an alternative to synaptic plasticity hypothesis | Scientific Reports

2022-05-06T01:52:43+00:00

Synaptic plasticity is a long-lasting core hypothesis of brain learning that suggests local adaptation between two connecting neurons and forms the foundation of machine learning. The main complexity of synaptic plasticity is that synapses and dendrites connect neurons in series and existing experiments cannot pinpoint the significant imprinted adaptation location. We showed efficient backpropagation and Hebbian learning on dendritic trees, inspired by experimental-based evidence, for sub-dendritic adaptation and its nonlinear amplification. It has proven to achieve success rates approaching unity for handwritten digits recognition, indicating realization of deep learning even by a single dendrite or neuron. Additionally, dendritic amplification practically generates an exponential number of input crosses, higher-order interactions, with the number of inputs, which enhance success rates. However, direct implementation of a large number of the cross weights and their exhaustive manipulation independently is beyond existing and anticipated computational power. Hence, a new type of nonlinear adaptive dendritic hardware for imitating dendritic learning and estimating the computational capability of the brain must be built.

High Static Magnetic Field Can Relieve Anxiety

2022-05-01T21:00:17+00:00

Exposure to high static magnetic fields alleviated anxiety and improved both spatial and social memory in mice within two months of exposure.

Simple, Computationally-Light Model Can Simulate Complex Brain Cell Responses

2022-04-18T19:48:16+00:00

The Izhikevich neuron model allows the simulation of both periodic and quasi-periodic responses in neurons at lower computational cost.

How Does the Brain Know Whether Our Actions Actually Make a Difference?

2022-03-10T20:34:45+00:00

Findings reveal how the brain calculates controllability based on neural activity and behavior.

Short- and Long-Range Connections Differentially Modulate the Dynamics and State of Small-World Networks

2022-01-25T04:42:29+00:00

The human brain contains billions of neurons that flexibly interconnect to support local and global computational spans. As neuronal activity propagates through the neural medium, it approaches a critical state hedged between ordered and disordered system regimes. Recent work demonstrates that this criticality coincides with the small-world topology, a network arrangement that accommodates both local (subcritical) and global (supercritical) system properties. On one hand, operating near criticality is thought to offer several neurocomputational advantages, e.g., high-dynamic range, efficient information capacity, and information transfer fidelity. On the other hand, aberrations from the critical state have been linked to diverse pathologies of the brain, such as post-traumatic epileptiform seizures and disorders of consciousness. Modulation of brain activity, through neuromodulation, presents an attractive mode of treatment to alleviate such neurological disorders, but a tractable neural framework is needed to facilitate clinical progress. Using a variation on the generative small-world model of Watts and Strogatz and Kuramoto's model of coupled oscillators, we show that the topological and dynamical properties of the small-world network are divided into two functional domains based on the range of connectivity, and that these domains play distinct roles in shaping the behavior of the critical state. We demonstrate that short-range network connections shape the dynamics of the system, e.g., its volatility and metastability, whereas long-range connections drive the system state, e.g., a seizure. Together, these findings lend support to combinatorial neuromodulation approaches that synergistically normalize the system dynamic while mobilizing the system state.

Why Neurons Consume So Much Fuel Even When at Rest

2021-12-03T22:35:45+00:00

Synaptic vesicles are a major source of energy consumption in inactive neurons, a new study reports.

Neural Network Models of the Future – The Key to Unlocking How Our Brain Works

2021-08-22T00:07:40+00:00

Researchers discuss different current neural network models and consider the steps that need to be taken to make them more realistic, and thus more useful, as possible.

Brain Connectivity Can Build Better AI

2021-08-09T22:04:36+00:00

Artificial neural networks modeled on human brain connectivity can effectively perform complex cognitive tasks.

Cell Structure Previously Associated With Disease Actually Improves Brain Function

2021-07-10T20:59:51+00:00

Axonal swelling in the Purkinje cells of mice had no detrimental impact on firing rate or the speed at which axons transmit signals. At peak firing rate, axons with swellings were less likely to fail than those without.

Scientists Discover a New Class of Memory Cells in the Brain

2021-07-01T20:56:11+00:00

Researchers have identified a novel population of neurons in the temporal pole that links facial perception to long-term memory.

Physics - Statistical Mechanics Built on Sand

2021-06-29T06:43:57+00:00

Fly Brains Make Predictions, Possibly Using Universal Design Principles

2021-05-22T21:18:43+00:00

Findings suggest prediction may be a general feature of animal nervous systems in supporting quick behavioral changes.

Brain’s ‘Background Noise’ May Hold Clues to Persistent Mysteries | Quanta Magazine

2021-05-14T05:50:48+00:00

t a sleep research symposium in January 2020, Janna Lendner presented findings that hint at a way to look at people’s brain activity for signs of the boundary between wakefulness and unconsciousness. For patients who are comatose or under anesthesia, it can be all-important that physicians make that distinction correctly. Doing so is trickier than it might sound, however, because when someone is in the dreaming state of rapid-eye movement (REM) sleep, their brain produces the same familiar, smoothly oscillating brain waves as when they are awake.

Evidence for Quasicritical Brain Dynamics

2021-03-01T10:00:00+00:00

Author(s): Leandro J. Fosque, Rashid V. Williams-García, John M. Beggs, and Gerardo Ortiz

A constant bombardment of stimuli drives the brain’s dynamics away from a critical point to a “quasicritical” state.

[Phys. Rev. Lett. 126, 098101] Published Mon Mar 01, 2021

A 'consciousness conductor' synchronizes and connects mouse brain areas - Neuroscience News

2020-05-12T12:00:19+00:00

Mouse study reveals slow-wave brain activity, which is indicative of sleep and resting states, is controlled by the claustrum. The synchronization of active and silent states across the brain via the slow waves contributes to consciousness.

Memory Transferred between Snails, Challenging Standard Theory of How the Brain Remembers - Scientific American

2018-05-21T05:04:34+00:00

UCLA neuroscientists reported Monday that they have transferred a memory from one animal to another via injections of RNA, a startling result that challenges the widely held view of where and how memories are stored in the brain.

長庚大學發現大腦記憶形成機制失智新見解登國際期刊

2017-08-10T22:00:00+00:00

長庚大學吳嘉霖副教授團隊利用果蠅研究長期記憶形成的機制時，發現短、長期記憶的形成是由兩套截然不同的大腦神經迴路與分子機制所控制，也就是說，長期記憶並非由短期記憶轉化而來。這項重要研究成果顛覆以往科學界對於記憶形成的認知，卻也合理解釋老年失智的臨床病徵，研究成果獲得肯定，登上國際頂尖期刊「自然通訊」(Nature Communications)，引起關注。

Hacking the human brain -- lab-made synapses for artificial intelligence

2017-06-28T04:00:00+00:00

One of the greatest challenges facing artificial intelligence development is understanding the human brain and figuring out how to mimic it. Now, one group reports in ACS Nano that they have developed an artificial synapse capable of simulating a fundamental function of our nervous system -- the release of inhibitory and stimulatory signals from the same 'pre-synaptic' terminal.

Working Memory: How You Keep Things "In Mind" Over the Short Term

2017-06-05T15:00:00+00:00

Given its central role in our mental life working memory may become important in our quest to understand consciousness itself

-- Read more on ScientificAmerican.com

Feds unveil rule requiring cars to ‘talk’ to each other | TheHill

2016-12-14T06:44:30+00:00

The Obama administration released a long-awaited rule on Tuesday requiring all new vehicles to have communication technology that allows them to “talk” to each another, which officials say could prevent tens of thousands of crashes each year. The proposal calls for all new light-duty cars and trucks to eventually be equipped with vehicle-to-vehicle (V2V) technology, a safety system that enables cars to send wireless signals to each other, anticipate each other’s moves and thus avoid crashes.

Neurons in the human eye are organized for error correction

2016-11-17T05:00:00+00:00

Neurons found in the human eye naturally display a form of error correction in the collective visual signals they send to the brain, according to a new study in PLOS Computational Biology.

Brain's Support Cells Could Explain Mysterious "Spreading Pain"

2016-11-11T14:15:00+00:00

Scientists uncover how non-neuronal cells induce synaptic plasticity in pain circuits, potentially across long distances

-- Read more on ScientificAmerican.com

What Experts Wish You Knew about False Memories

2016-08-08T12:45:00+00:00

Credit: Pixabay

Imaging the brain at multiple size scales

2016-07-26T04:00:00+00:00

MIT researchers have developed a new technique for imaging brain tissue at multiple scales, allowing them to image molecules within cells or take a wider view of the long-range connections between neurons. The technique, magnified analysis of proteome, should help scientists chart the connectivity and functions of neurons in the human brain.

Change in the brain: Astrocytes finally getting the recognition they deserve

2016-04-25T04:00:00+00:00

Researchers at the RIKEN Brain Science Institute in Japan have demonstrated that astrocytes help control the strength of connections between neurons. Published in Proceedings of the National Academy of Sciences, the study used cultured cells and brain slices to show that astrocytes in the hippocampus regulate changes in the brain brought on by neural activity.

Complex learning dismantles barriers in the brain

2016-03-15T04:00:00+00:00

Scientists at the Jagiellonian University in Poland taught Braille to sighted individuals and found that learning such a complex tactile task activates the visual cortex, when you'd only expect it to activate the tactile one.

Has DeepMind Really Passed Go? — Backchannel — Medium

2016-02-01T08:48:15+00:00

In the very same week that Artificial Intelligence lost one of its greatest pioneers, Marvin Minsky, it saw major progress on a decades-old challenge of playing human-level Go. There is much to shout about, but also a lot of hype and confusion about what we just saw. With so much at stake as people try to handicap the future of AI, and what it means for the future of employment and possibly even the human race, it’s important to understand what was and was not yet accomplished.

New insights into the molecular basis of memory

2015-12-17T05:00:00+00:00

Scientists from the German Center for Neurodegenerative Diseases have shed new light on the molecular basis of memory. Their study confirms that the formation of memories is accompanied by an altered activity of specific genes. In addition, they found an unprecedented amount of evidence that supports the hypothesis that chemical labels on the backbone of the DNA (so-called DNA methylation) may be the molecular basis of long-term memory. These findings are reported in Nature Neuroscience.

New research helps to explain how temperature shifts the circadian clock

2015-12-01T05:00:00+00:00

One important aspect of the internal time-keeping system continues to perplex scientists: its complex response to temperature, which can shift the clock forward or backward, but cannot change its 24-hour period. New experiments help explain how this is possible.

Leading theory of consciousness rocked by oddball study

2015-11-04T18:00:00+00:00

Scientist show that widespread activity occurs in the brain even during unconscious processing – which shouldn't happen if our theories of consciousness are correct

'Odometer neurons' encode distance traveled and elapsed time

2015-11-04T05:00:00+00:00

Animals navigate by calculating their current position based on how long and how far they have traveled and a new study on treadmill-running rats reveals how: neurons called grid cells integrate information about time and distance to support memory and spatial navigation, even in the absence of visual landmarks. The findings, published Nov. 4 in the journal Neuron, challenge currently held views of the role of grid cells in the brain.

Do general anaesthetics trigger a phase transition in the brain?

2015-09-07T14:51:52+00:00

Model suggests tiny change in communication could have large effect on neuron interaction

Researchers find the organization of the human brain to be nearly ideal | news @ Northeastern

2015-07-07T15:14:54+00:00

Functioning brain follows famous sand pile model

2015-06-22T04:00:00+00:00

In 1999 Danish scientist Per Bak made the startling proposal that the brain remained stable for much the same reason a sand pile does; many small avalanches hold it at a balance point, where -- in the brain's case -- information processing is optimized. Now scientists have showed for the first time that a brain receiving and processing sensory input follows these dynamics.

Nerve cells use each other as maps

2015-05-19T04:00:00+00:00

When nerve cells form in an embryo they have to be guided to their final position by navigating a kind of molecular and cellular 'map' in order to function properly. In a recent research study published in Nature Communications neurobiologist Sara Wilson, Umeå University in Sweden, found that during embryonic development different parts of the nerve cell are important for guiding other nerve cells into their physical positions.

A First Big Step Toward Mapping the Human Brain | WIRED

2015-05-16T15:29:50+00:00

It’s a long, hard road to understanding the human brain, and one of the first milestones in that journey is building a … database.

Neuron groups, not single cells, maintain brain stability

2015-03-02T05:00:00+00:00

Disruptions in brain stability cause disorders such as epilepsy, but precious little is known about homeostasis, the brain's regulatory system. Now a new study from Tel Aviv University finds that homeostatic regulation occurs mainly in groups of neurons rather than in the individual neurons themselves. Understanding the principles and mechanisms involved in neuronal homeostasis may lead to new approaches in the treatment of brain disorders like Alzheimer's disease.

Why movies look weird at 48fps, and games are better at 60fps, and the uncanny valley… | Accidental Scientist

2014-12-25T00:42:53+00:00

It should be safe to conclude that humans can see frame rates greater than 24 fps. The next question is: why do movies at 48 fps look "video-y," and why do movies at 24 fps look "dreamy" and "cinematic." Why are games more realistic at 60 fps than 30 fps? Simon Cooke from Microsoft (Xbox) Advanced Technology Group has an interesting theory to explain this all. Your eyes oscillate a tiny amount, ranging from 70 to 103 Hz (on average 83.68 Hz). So here's the hypothesis: The ocular microtremors wiggle the retina, allowing it to sample at approximately 2x the resolution of the sensors. Showing someone pictures that vary at less than half the rate of the oscillation means we're no longer receiving a signal that changes fast enough to allow the supersampling operation to happen. So we're throwing away a lot of perceived-motion data, and a lot of detail as well. Some of the detail can be restored with temporal antialiasing and simulating real noise, but ideally Cooke suggests going with a high enough frame rate (over 43 fps) and if possible, a high resolution.

Distinguishing cause from effect using observational data: methods and benchmarks

2014-12-20T03:23:08+00:00

The discovery of causal relationships from purely observational data is a fundamental problem in science. The most elementary form of such a causal discovery problem is to decide whether X causes Y or, alternatively, Y causes X, given joint observations of two variables X, Y . This was often considered to be impossible. Nevertheless, several approaches for addressing this bivariate causal discovery problem were proposed recently. In this paper, we present the benchmark data set CauseEffectPairs that consists of 88 different "cause-effect pairs" selected from 31 datasets from various domains. We evaluated the performance of several bivariate causal discovery methods on these real-world benchmark data and on artificially simulated data. Our empirical results provide evidence that additive-noise methods are indeed able to distinguish cause from effect using only purely observational data. In addition, we prove consistency of the additive-noise method proposed by Hoyer et al. (2009).

Decreased segregation of brain systems across the healthy adult lifespan

2014-12-07T16:23:28+00:00

The brain is a large-scale network, not unlike many social or technological networks. Just like social networks, brain networks contain subnetworks or systems of highly related or interacting nodes (in the case of brains, nodes may represent neurons or brain areas). Using functional MRI to measure functional correlations between brain areas during periods of rest, we describe differences in brain network organization in a large group of individuals sampled across the healthy adult lifespan (20–89 y). We characterize a measure of system segregation, reflecting the degree to which the systems share connections among one another. Increasing age is accompanied by decreasing segregation of brain systems. Importantly, system segregation is predictive of measures of long-term memory function, independent of age.

Penn researchers untangle the biological effects of blue light

2014-10-20T04:00:00+00:00

Blue light can both set the mood and set in motion important biological responses. Researchers at the University of Pennsylvania's School of Medicine and School of Arts and Sciences have teased apart the separate biological responses of the human eye to blue light, revealing an unexpected contest for control.

the neuroscience of consciousness

2014-10-13T00:06:16+00:00

Consciousness has traditionally been a philosophical question due largely to a lack of information regarding the specific details of brain function and how they correlate to the everyday experience in general. With models and techniques from experimental neurobiology and paradigms from the complexity and information sciences, neuroscientists have begun to produce empirical results that should inform any philosophical speculation.

Neural activity predicts the timing of spontaneous decisions

2014-10-01T04:00:00+00:00

Researchers have discovered a new type of brain activity that underlies the timing of voluntary actions, allowing them to forecast when a spontaneous decision will occur more than a second in advance. 'Experiments like this have been used to argue that free will is an illusion, but we think that this interpretation is mistaken,' says Zachary Mainen, a neuroscientist at the Champalimaud Centre for the Unknown, in Lisbon, Portugal, who led the research, published on Sept. 28, 2014, in the journal Nature Neuroscience.

What happens in our brain when we unlock a door?

2014-10-01T04:00:00+00:00

People who are unable to button up their jacket or who find it difficult to insert a key in lock suffer from a condition known as apraxia. This means that their motor skills have been impaired -- as a result of a stroke, for instance. Scientists in Munich have now discovered that there is a specific network in the brain for using tools. Their findings have been published in the Journal of Neuroscience.

Using rhythmic brain activity to track memories in progress

2014-06-24T01:12:48+00:00

Using electroencephalogram (EEG) electrodes attached to the scalps of 25 student subjects, a UO team led by psychology doctoral student David E. Anderson captured synchronized neural activity while they held a held a simple oriented bar located within a circle in short-term memory. The team, by monitoring these alpha rhythms, was able to decode the precise angle of the bar the subjects were locking onto and use that brain activity to predict which individuals could store memories with the highest quality or precision.

Clever Suppression in the Brain

2014-06-15T16:01:45+00:00

Diversity of inhibiting nerve cells allows for more complex information processing: The hippocampus is a small structure in the brains of mammals that plays a crucial role in processing input from our senses and allows perceptions to be stored as memories. Nerve cells that inhibit the activity of other cells have now been shown to play a much larger and more complex role in these processes than previously assumed.

neuro

Neural criticality from effective latent variables. (arXiv:2301.00759v3 [q-bio.NC] UPDATED)

Sequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule

Detecting Hidden Brain States With Mathematical Models

Our Memory for Objects Might Be Better Than We Think

How the Brain Stores Remote Fear Memory

Scientists Capture Detailed Snapshots of Mouse Brain Cells Nibbling on Neurons

Unique Features of Octopus Create an Entirely New Way of Designing a Nervous System

Human brain cells in a dish learn to play Pong in real time -- ScienceDaily

Neuroscience data analysis in the cloud

Scientists Break the Direction of Time Down to the Cellular Level in Mind-Bending Study

Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures

Emergent organization of receptive fields in networks of excitatory and inhibitory neurons. (arXiv:2205.13614v1 [q-bio.NC])

Deep Residual Convolutional Neural Networks for Brain–Computer Interface to Visualize Neural Processing of Hand Movements in the Human Brain

Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines. (arXiv:2205.06313v1 [q-bio.MN])

Efficient dendritic learning as an alternative to synaptic plasticity hypothesis | Scientific Reports

High Static Magnetic Field Can Relieve Anxiety

Simple, Computationally-Light Model Can Simulate Complex Brain Cell Responses

How Does the Brain Know Whether Our Actions Actually Make a Difference?

Short- and Long-Range Connections Differentially Modulate the Dynamics and State of Small-World Networks

Why Neurons Consume So Much Fuel Even When at Rest

Neural Network Models of the Future – The Key to Unlocking How Our Brain Works

Brain Connectivity Can Build Better AI

Cell Structure Previously Associated With Disease Actually Improves Brain Function

Scientists Discover a New Class of Memory Cells in the Brain

Physics - Statistical Mechanics Built on Sand

Fly Brains Make Predictions, Possibly Using Universal Design Principles

Brain’s ‘Background Noise’ May Hold Clues to Persistent Mysteries | Quanta Magazine

Evidence for Quasicritical Brain Dynamics

A 'consciousness conductor' synchronizes and connects mouse brain areas - Neuroscience News

Memory Transferred between Snails, Challenging Standard Theory of How the Brain Remembers - Scientific American

長庚大學發現大腦記憶形成機制 失智新見解登國際期刊

Hacking the human brain -- lab-made synapses for artificial intelligence

Working Memory: How You Keep Things "In Mind" Over the Short Term

Feds unveil rule requiring cars to ‘talk’ to each other | TheHill

Neurons in the human eye are organized for error correction

Brain's Support Cells Could Explain Mysterious "Spreading Pain"

What Experts Wish You Knew about False Memories

Imaging the brain at multiple size scales

Change in the brain: Astrocytes finally getting the recognition they deserve

Complex learning dismantles barriers in the brain

Has DeepMind Really Passed Go? — Backchannel — Medium

New insights into the molecular basis of memory

New research helps to explain how temperature shifts the circadian clock

Leading theory of consciousness rocked by oddball study

'Odometer neurons' encode distance traveled and elapsed time

Do general anaesthetics trigger a phase transition in the brain?

Researchers find the organization of the human brain to be nearly ideal | news @ Northeastern

Functioning brain follows famous sand pile model

Nerve cells use each other as maps

A First Big Step Toward Mapping the Human Brain | WIRED

Neuron groups, not single cells, maintain brain stability

Why movies look weird at 48fps, and games are better at 60fps, and the uncanny valley… | Accidental Scientist

Distinguishing cause from effect using observational data: methods and benchmarks

Decreased segregation of brain systems across the healthy adult lifespan

Penn researchers untangle the biological effects of blue light

the neuroscience of consciousness

Neural activity predicts the timing of spontaneous decisions

What happens in our brain when we unlock a door?

Using rhythmic brain activity to track memories in progress

Clever Suppression in the Brain

長庚大學發現大腦記憶形成機制失智新見解登國際期刊