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#neuroscience

40 posts34 participants1 post today
Public
Chris Simpson

Had a non fiction book on my shelf for a while that I couldn't get the audiobook for, but now I'm traveling I'm finally able to get into it

It's called The Man Who Mistook His Wife For A Hat (And Other Clinical Tales) by Oliver Sacks

It's a collection of real clinical cases and the reflections of the attending neurologist (the author)

It's both a fascinating insight into the nature of experience and how that can be affected by a brain injury or disease, and a series of touching stories about helping people find peace when nothing makes sense around them

#neuroscience
Public
Theresa Desrochers

Save the date for a FREE virtual workshop @NIH: Reasoning Algorithms Across Species, Diagnoses, and Development: Theoretical Frameworks Informing Causal Manipulations, April 23 11am-5pm. I'm looking forward to it! #neuroscience 🧠 🧪

obssr.od.nih.gov/news-and-even

Office of Behavioral and Social Sciences ResearchReasoning Algorithms Across Species, Diagnoses, and Development: Theoretical Frameworks Informing Causal ManipulationsDescriptionThe goal of this workshop is to advance our understanding of the brain's reasoning algorithms, explore effects of brain disorders on these algorithms, and discuss whether computational models of reasoning can suggest novel interventions.
Public
BGDoncaster

Whoa! LOTS to unpack here. Weekend Reading!

Anthropic reveals research how AI systems process information and make decisions. AI models can perform a chain of reasoning, can plan ahead, and sometimes work backward from a desired outcome. The research also provides insight into why language models hallucinate.

Interpretation techniques called “circuit tracing” and “attribution graphs” enable researchers to map out the specific pathways of neuron-like features that activate when models perform tasks. See the links below for details.

Summary Article: venturebeat.com/ai/anthropic-s

Circuit Tracing: transformer-circuits.pub/2025/

Research Overview: transformer-circuits.pub/2025/ #AI #Anthropic #LLMs #Claude #ChatGPT #CircuitTracing #neuroscience

AI Circuit Tracing
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Philo Sophies

“Free Willy - Call of freedom for the #free #will”

In this essay, I deal firstly with “the #philosophical #problem of #freedom of will”, then with the #empirical attacks on freedom of will” and finally with the ‘latest #results of #cognitive #neuroscience’ of #self-control. The whole thing is then rounded off with “proposals for overcoming the #determinism-freedom-of-will #dualism.

More at: philosophies.de/index.php/2023

picture of an orca whale
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El Duvelle Neuro

5 #NeuroJobs in #Glasgow !! Please share!

  • 3 in cognitive neuroscience/psychology.
  • 1 in psychology.
  • 1 in animal behavioural neuroscience with a particular emphasis on teaching

Appointments can range from Grade 7-9 (Lecturer/Senior Lecturer in the UK; assistant/associate professor in the US) to Grade 10 (full Professor)

nature.com/naturecareers/job/1

Closing Date: 12 May 2025

Nature CareersProfessor, Senior Lecturer/Lecturer and Lecturer posts - Glasgow City (GB) job with University of Glasgow | 12838283University of Glasgow College of Medical, Veterinary and Life Sciences  School of Psychology & Neuroscience Professor in Cognitive Neuroscience/Psy...
#UofG#UofGPsychNeuro#Neuroscience
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El Duvelle

I'm trying to read a #Neuroscience paper published by #Wiley and it's showing me a banner that says only "healthcare professionals" should be reading the paper. What's up with that? Researchers are not allowed to read papers anymore? 🤔

Impossible to find a way to contact Wiley about it, but maybe someone out there will know them and might be able to ask what is happening?

The paper: Locomotor action sequences impact the scale of
representation in hippocampus and posterior parietal cortex #NitzLab #WileyOnlineLibrary #Academia

Screenshot of a banner seen on the Wiley publisher website when accessing a neuroscience article saying: "This material is only for use by healthcare professionals. By continuing to view this site you are confirming that you are a healthcare professional."
Public
Nate Gaylinn

I really enjoyed this podcast on glial cells in the brain (manyminds.libsyn.com/the-other)

Mostly we talk about brains being made of neurons, but it's much more complicated than that. There are many cell types, with different roles. Glia seem to help with development, management, and pruning of neurons throughout life.

One of my lab groups studies "meta learning," or ways of optimizing the design of artificial neural networks to suit a given learning challenge. Some of the techniques we use involve these sorts of dual systems: a neural network, and then a process that manages the growth, pruning, and activation of that network.

Those algorithms are offshoots from artificial neural networks and their very artificial and simplified model of the brain. So, I'm fascinated that from that starting point, we may have rediscovered what nature already had.

I wonder if glia really are an analog to what we're doing, and whether they have anything to teach us about meta learning.

manyminds.libsyn.comMany Minds: The other half of the brainNeurons have long enjoyed a kind of rock star status. We think of them as the most fundamental units of the brain—the active cells at the heart of brain function and, ultimately, at the heart of behavior, learning, and more. But neurons are only part of the story—about half the story, it turns out. The other half of the brain is made up of cells called glia. Glia were long thought to be important structurally but not particularly exciting—basically stage-hands there to support the work of the neurons. But in recent decades, at least among neuroscientists, that view has faded. In our understanding of the brain, glia have gone from stage-hands to co-stars.   My guest today is . Nicola is a molecular neuroscientist and Associate Professor at the Salk Institute in La Jolla, California. She and her lab study the role of glial cells—especially astrocytes—in brain function and dysfunction.   Here, Nicola and I talk about how our understanding and appreciation of glial cells has changed. We do a bit of Brain Cells 101, reviewing the main division between neurons and glia and then sketching the subtypes within each category. We discuss the different shapes and sizes of glial cells, as well as the different functions. Glia are an industrious bunch. They’re involved in synapse formation and pruning, the production of myelin, the repair of injuries, and more. We also talk about how glial cells have been implicated in various forms of brain dysfunction, from neurodegeneration to neurodevelopmental syndromes. And how, as a result, these cells are attracting serious attention as a site for therapeutic intervention.   Well, it's that time of year again folks. Applications are now open for the 2025 Diverse Intelligences Summer Institute, or DISI. This is an intense program—highly interdisciplinary, highly international—for scholars and storytellers interested in all forms and facets of intelligence. If you like thinking about minds, if you like thinking about humans and animals and plants and AIs and collectives and ways they’re alike and different—you would probably like DISI. For more info, check out —that's D-I-S-I dot org. Review of applications begins March 1st, so don't dally too too long.   Alright friends—on to my conversation with Dr. Nicola Allen. Enjoy!   A transcript of this episode is available .   Notes and links 3:00 – Correction: “glia” actually comes from the Greek—not the Latin—for “glue.” 3:30 – See this short on glia by Dr. Allen and Dr. Ben Barres. For a bit of the history of how glial cells were originally conceived, see  on Ramón y Cajal’s contributions to glia research. 10:00 – On the nascent field of “neuroimmunology,” see . 14:00 – On the idea that “90% of brain cells are glia” see by (former ) Suzana Herculano-Houzel. 18:00 – The root “oligo” in “oligodendrocyte” means “few” (and is thus the same as the “olig” in, e.g., “oligarchy"). It is not related to the “liga-” in “ligament.” 28:00 – On the idea that the glia-neuron ratio changes as brains grow more complex, see again the by Dr. Herculano-Houzel. 30:00 – See Dr. Allen’s on the idea of glia as “architects.” See also Dr. Allen’s on the idea of glia as “sculptors.” 33:00 – See Dr. Allen’s on the idea of the “tripartite synapse.” 42:00 – A recent reviewing the phenomenon of adult neurogenesis.  48:00 –  See Dr. Allen’s of the role of astrocytes in neurodegeneration. 51:30 – A on the roles of APOE in Alzheimer’s.   Recommendations , edited by Beth Stevens, Kelly R. Monk, and Marc R. Freeman   Many Minds is a project of the , which is made possible by a generous grant from the John Templeton Foundation to Indiana University. The show is hosted and produced by , with help from Assistant Producer and with creative support from DISI Directors Erica Cartmill and Jacob Foster. Our artwork is by . Our transcripts are created by .   Subscribe to Many Minds on Apple, Stitcher, Spotify, Pocket Casts, Google Play, or wherever you listen to podcasts. You can also now subscribe to the Many Minds newsletter ! We welcome your comments, questions, and suggestions. Feel free to email us at: manymindspodcast@gmail.com.    For updates about the show, visit or follow us on Twitter () or Bluesky ().
#science#podcast#ml
Public
Fabrice Tshimanga

Exciting news, our paper is out!

"Behavioral Clusters and Lesion Distributions in Ischemic Stroke, Based on NIHSS Similarity Network" on Springer Journal of Healthcare Informatics Research rdcu.be/efgma

With my co-first-author Andrea Zanola and co-authors, we explore the relations between behavioral measures of impairment after stroke, and the underlying brain lesions.
Rather than focusing on covariances at the population level, we first cluster individual behavioral phenotypes, and then explore the typical and significant lesions of each cluster.

Our technique, Repeated Spectral Clustering is performed on a similarity network (derived from the General Distance Measure, handy for ordinal scales!), and the partitions are statistically robust thanks to the aggregation of results from multiple random initializations.

We end up with 5 clusters, 3 of which show reknown principal components of deficits (Left Motor, Righ Motor, Language), and their associate lesions.

Interestingly, this multi-item and multimodal approach allows to distinguish different etiologies for the same deficits, thanks to their different behavioral associations, and the different lesions characterizing each cluster. Even when the single NIHSS measure is a bit "vague"...

We hope that popularizing the General Distance Measure, Repeated Spectral Clustering and this clustering perspective aside of PCA / CCA studies can inspire multimodal approaches in other neuroscientific and biomedical domains!

Many thanks to our co-authors, Antonio Luigi Bisogno, Silvia Facchini, Lorenzo Pini, Manfredo Atzori and Maurizio Corbetta for data, analytic and medical insights, and their guidance throughout the whole process!

A network of 172 nodes with 5 clusters of eightened connection, and lighter connections across the 5 clusters. Each cluster is a set of subjects with similar post-stroke impairments
5 radarplots with median profiles of impairments after stroke, for 5 clusters with similar symptoms. Below each radarplot, a heatmap of most frequently lesioned areas of the brain, wrt the cluster
#stroke#neuroscience#clustering
Public
Albert Cardona

Even worms can minimize effort when they have the choice – here, assessed when feeding:

"C. elegans food choice exhibits effort discounting-like behavior", Millet et al. 2025 (Shawn Lockery's lab)

biorxiv.org/content/10.1101/20

bioRxiv · C. elegans food choice exhibits effort discounting-like behaviorCost-benefit decisions are ubiquitous in both human and animal behavior. Economists have developed formal models of cost-benefit decision-making by focusing on discounting behavior, the devaluation of a reward based on the costs associated with it. The phylogenetic limits of discounting behavior remain unknown. Here, we provide evidence that the nematode C. elegans exhibits behavior closely resembling effort discounting. Given a choice between food options that are easy or difficult to consume, worms devalue the latter in a manner predicted by economic models. We identified a plausible mechanism for this behavior based on differential rates of leaving food patches and demonstrated that this mechanism is disrupted by deficits in dopamine signaling, as in rodents. Together, these results establish C. elegans as a potential invertebrate model for discounting behavior and set new phylogenetic bounds on this type of cost-benefit decision-making. ### Competing Interest Statement The authors have declared no competing interest.
#neuroscience#Celegans
Public
Albert Cardona

"A spiking neural network model for proprioception of limb kinematics in insect locomotion", by van der Veen et al. 2025.

biorxiv.org/content/10.1101/20

bioRxiv · A spiking neural network model for proprioception of limb kinematics in insect locomotionProprioception plays a key role in all behaviours that involve the control of force, posture or movement. Computationally, many proprioceptive afferents share three common features: First, their strictly local encoding of stimulus magnitudes leads to range fractionation in sensory arrays. As a result, encoding of large joint angle ranges requires integration of convergent afferent information by first-order interneurons. Second, their phasic-tonic response properties lead to fractional encoding of the fundamental sensory magnitude and its derivatives (e.g., joint angle and angular velocity). Third, the distribution of disjunct sensory arrays across the body accounts for distributed encoding of complex movements, e.g., at multiple joints or by multiple limbs. The present study models the distributed encoding of limb kinematics, proposing a multi-layer spiking neural network for distributed computation of whole-body posture and movement. Spiking neuron models are biologically plausible because they link the sub-threshold state of neurons to the timing of spike events. The encoding properties of each network layer are evaluated with experimental data on whole-body kinematics of unrestrained walking and climbing stick insects, comprising concurrent joint angle time courses of 6 × 3 leg joints. The first part of the study models strictly local, phasic-tonic encoding of joint angle by proprioceptive hair field afferents by use of Adaptive Exponential Integrate-and-Fire neurons. Convergent afferent information is then integrated by two types of first-order interneurons, modelled as Leaky Integrate-and-Fire neurons, tuned to encode either joint position or velocity across the entire working range with high accuracy. As in known velocity-encoding antennal mechanosensory interneurons, spike rate increases linearly with angular velocity. Building on distributed position/velocity encoding, the second part of the study introduces second- and third-order interneurons. We demonstrate that simple combinations of two or three position/velocity inputs from disjunct arrays can encode high-order movement information about step cycle phases and converge to encode overall body posture. Author summary When stick insects climb through a bramble bush at night, they successfully navigate through highly complex terrain with little more sensory information than touch and proprioception of their own body posture and movement. To achieve this, their central nervous system needs to monitor the position and motion of all limbs, and infer information about whole-body movement from integration in a multi-layer neural network. Although the encoding properties of some proprioceptive inputs to this network are known, the integration and processing of distributed proprioceptive information is poorly understood. Here, we use a computational model of a spiking neural network to simulate peripheral encoding of 6 × 3 joint angles and angular velocities. The second part of the study explores how higher-order information can be integrated across multiple joints and limbs. For evaluation, we use experimental data from unrestrained walking and climbing stick insects. Spiking neurons model the key response properties known from their real biological counterparts. In particular, we show that the first integration layer of the model is able to encode joint angle and velocity both linearly and accurately from an array of phasic-tonic input elements. The model is simple, accurate and based, where possible, on biological evidence. ### Competing Interest Statement The authors have declared no competing interest.
#neuroscience#proprioception#insects
Public
Earl K. Miller

And we need to embrace the likely possibility that brains are more than connectivity patterns and their weightings. That is the start, not the end.
Accepting “the bitter lesson” and embracing the brain’s complexity
thetransmitter.org/neuroai/acc
#neuroscience

Data streams into a transparent box.
The Transmitter: Neuroscience News and Perspectives · Accepting “the bitter lesson” and embracing the brain’s complexityBy Eva Dyer
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