Interwoven neurons of the striatum: communication between patch and matrix compartments

Neuromodulators are a class of signaling molecules that typically operate though second messenger signaling cascades, inducing long-lasting signals over potentially widespread areas. Some of the major ones may be familiar – dopamine, serotonin, acetylcholine, for example. However, there is a wide diversity of neuromodulators and their effects. One researcher attempting to de-mystify this class of molecules is Dr. Matthew Banghart, Assistant Professor in Neurobiology at UCSD studying neuromodulatory signaling pathways and their influence on neural circuit function, specifically in the mammalian basal ganglia. The basal ganglia are a group of brain nuclei critical that are implicated in a wide range of functions, including generation of purposeful movements, reinforcing behaviors that maximize reward, and motivational and habitual control. Several different neuromodulators are well known to act on this system. One important nucleus of the basal ganglia is the striatum, which is the principal input nucleus and integrates cortical and thalamic input to the basal ganglia. The striatum is anatomically and functionally complex with several levels of organization. One level is its division of neurons into patch and matrix compartments, where patches exist as interconnected tubes running through the matrix, much like the weaving of a textile. This organization is conserved across species and is therefore likely to play an important role in basal ganglia function.

Patch and matrix compartments are known to express different biochemical markers but the causes and consequences of this are not well understood. Furthermore, it is known that both compartments contribute to the direct and indirect output pathways of the striatum. Therefore, the functional consequences of patch-matrix compartmentalization are of interest in understanding local basal ganglia circuitry. In 2015 Dr. Banghart et al. published a paper titled “Enkephalin Disinhibits Mu Opioid Receptor-Rich Striatal Patches via Delta Opioid Receptors” which revealed the role of the neuromodulator enkephalin (enk) on patch output in dorsal striatum. Enkephalin is involved in the body’s response to harmful stimuli and is expressed in striatal neurons across species. In humans, enk-expressing striatal projection neurons (SPNs) are part of the indirect pathway of basal ganglia circuitry, while neurons of the direct pathway express other signaling molecules. Importantly, striatal patches are known have a high level of mu opioid receptor (MOR) which binds enk, whereas enk itself is expressed in indirect pathway SPNs (iSPNS) in the matrix. Given clear enk and MORs distribution, it was hypothesized that enk signaling may represent a means of communication between compartments.

In order to study enk signaling, the researchers used a transgenic mouse line allowing for the immunohistochemical identification of both direct and indirect striatal pathways as well as matrix and patch compartments, and performed histochemical and electrophysiological techniques on brain slices. The group recorded synaptic currents in patches while electrically stimulating in patch and then matrix compartments, finding that matrix stimulation did not elicit responses in patches. This observation suggests that patches are synaptically isolated. The most important finding was that enk was shown to modulate inhibitory activity of direct SPNs (dSPN) (see figure below). By expressing channelrhodopsin in both indirect and direct SPNs and examining the effect of enk on optogenetically-evoked inhibitory post-synaptic currents (IPSCs) in both striatal neuron classes, they were able to observe strong suppression by enk of synaptic inhibition originating from iSPNs and weaker suppression on inhibition from dSPNs. Contrary to their hypothesis, it was found that the majority of iSPN modulation on inhibitory activity was mediated by delta opioid receptors (DORs), not MORs. In sum, matrix neurons release enk, which binds predominantly to DORs on iSPN neurons in patches, and these provide collateral input to patch dSPN neurons. The implications of this work are that at least one type of neuromodulator, enkephalin, is a mechanism for patch-matrix communication, potentially gating information flow in the striatum by activating patch-specific DORs.

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To hear about Dr. Banghart’s related projects, join us at his talk titled “Convergent neural pathways underlying pharmacological and cognitive pain modulation” this coming Tuesday May 19, 2020 at 4 pm via Zoom.

Written by Emma Boyd, a 1st year in the Neurosciences Graduate Program at UCSD.

Sonogenetics: A Powerful Tool for Manipulating Neurons with Ultrasound

Sreekanth Chalasani and his lab at the Salk Institute are primarily interested in behavior, and how neuronal circuits generate and produce certain behaviors. Their lab uses the roundworm, Caenorhabditis elegans (C. elegans), as their primary model system to study different types of behavior. C. Elegans has a much simpler nervous system, with only 302 neurons, which is substantially less compared to humans or other mammalian models and is easier to study. To study behavior, the current systems neuroscience field has multiple techniques to manipulate, monitor, and map existing neuronal populations. One of the most common techniques is optogenetics, which utilizes light in order to manipulate ion channels within neurons. However, optogenetic approaches require invasive surgical procedures in order to access deeper brain structures for light delivery. Most recently, Dr. Chalasani’s lab has been focused on developing a new technique called Sonogenetics, which utilizes ultrasound in order to manipulate targeted cells of interest.

Ultrasound is a widely used technique in clinical settings, as it is capable of traveling through skin and thin bone into deeper tissue. It thrives on being noninvasive, as well as being minimally damaging compared to other imaging methodologies. Ultrasound has also been used in research to stimulate clusters of neurons in vitro and neurons within other model organisms. This newly developed technique, Sonogenetics, is very similar to optogenetics, where light is used to selectively activate cells. However, sonogenetics utilizes low-frequency ultrasound, which is capable of traveling through the body with minimal scattering and signal loss. These ultrasound waves target a mechanotransduction channel, TRP-4, which is a calcium ion channel that is sensitive to low-pressure ultrasound. C. elegans normally express TRP-4 channels, which are opened with stretching of the body.

Normally, wild-type animals are insensitive to low-pressure ultrasound. However, when C. elegans were surrounded by gas-filled microbubbles, these microbubbles were effective in transducing the ultrasound stimuli. This ultrasound stimuli would cause a backward movement, which they call a reversal. They hypothesized that individual neurons could be activated through the TRP-4 channels due to the interaction between the ultrasound waves and the microbubbles. Shown in Figure 5a, animals lacking TRP-4 channels have a reduced number of reversals, suggesting that these TRP-4 channels are important for receiving ultrasound signal.

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Most recently, Dr. Chalasani’s lab is focused on expanding Sonogenetics to the mice model as well, which will expand the available neuroscience techniques available for dissection of the nervous system. To hear more about the work being done in Dr. Chalasani’s lab, please join us at 4:00 pm Tuesday May 5th on Zoom.

____________________________________________________________________________________________Written by Caroline Jia, a 1st year Neuroscience MSTP Student, working in Sung Han’s laboratory at the Salk Institute


Is it possible to predict behavior by reading neural activity?

Biological systems are in a constant state of flux and neuronal networks are dynamic, new neurons are added to circuits during development and during adulthood synaptic plasticity allows for formation of new, temporary connections and removal of the ones no longer needed. Understanding how the brain processes information is a challenging task that must add a constantly changing network, a dynamic microenvironment, and the continuous information inflow from the outside environment, to the already complex equation. Dr. Tatyana Sharpee at the Salk Institute conducts groundbreaking research integrating physics, mathematics and information theory with neural computations in order to understand how the brain processes sensory information. By understanding data from experiments, her lab develops new mathematical and statistical frameworks aimed to explain sensory processing and predict animal behavior. By using information theory her research seeks to understand how communication happens across different areas in the brain. The disruption in information processing leads to disease. Understanding how the information is processed and what leads to its disruption could help to develop brain-machine interfaces which could be used therapeutically in the future. Dr. Sharpee has taken different approaches to understand how the brain functions as a biological system, from object recognition involving visual stimuli to olfaction.

One approach the field has used in understanding how the sum of a complex neuronal network yields a functional operation is termed neuronal population vector. The neuronal population vector is a weighted vectorial sum of individual elements, neurons, and their activity and results in an estimated measure of behavior. Although this approach has advanced the field, it has some drawbacks such as discarding substantial information included in the responses of a neuronal population. This limits the understanding of how signal communication occurs between different areas within the central nervous system. By using information theory, Dr. Sharpee and her team have modified the population vector expression to achieve a blueprint for building circuits where signals can be read-out without information loss, an approach they have named sufficient population vector [2].

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The sufficient vector captures all information from diverse neural populations and with correlated variability across neurons. In all panels, they compare information transmitted by a population response (black line) with information transmitted by the sufficient population vector (red) and the standard population vector (dashed gray). Neural populations tuned to the same (a, c) or different (b, d) preferred stimuli. In (a) differences in neural tuning curves are due to differences in steepness values, whereas in (c) they are due to differences in thresholds. Dotted lines show the information values obtained by binning response variables. Dotted lines overlap with solid curves. (d) same as (b) but with noise correlations. Insets show example population tuning curves. Taken from Sharpee et. al. 2019.

To hear more about Dr. Sharpee’s sufficient population vector and recent projects, join us at her talk titled “Reading responses of large neural population without information loss” Tuesday April 21, 2020 at 4 pm via Zoom (

Written by Minerva Contreras a 1st year in the Neurosciences Graduate Program at UCSD.


[1] Mahan, M. Y., & Georgopoulos, A. P. (2014). Neuronal Population Vector. In Encyclopedia of Computational Neuroscience (pp. 1–7). Springer New York.

[2] Sharpee, Tatyana O., & Berkowitz, John A. (2019). Linking neural responses to behavior with information-preserving population vectors. Current Opinion in Behavioral Sciences29(C). doi:10.1016/j.cobeha

Keeping time in the visual system: computational modeling of thalamocortical connectivity

At this very moment, your brain is accomplishing amazing feats. You can see these words and effortlessly understand their meaning. Tomorrow and a week from now you’ll be able to remember parts of what you read. Understanding how the brain encodes, computes and retains information is one of the greatest challenges to neuroscience, and computational modeling is an increasingly important tool in tackling the complexity of the brain and the tasks it accomplishes. Throughout his career, Dr. Terry Sejnowski has contributed hugely to the development of computational neuroscience. His research continues to use innovative computational techniques, combined with experimental data, to elucidate how the brain accomplishes its computation feats. The breath of his lab’s research can begin to be appreciated by looking at their publications from 2019, featuring articles on topics ranging from the role of astrocytic intracellular signaling in long term memory, to identifying feedback projections in early olfactory sensation, to introducing a framework to construct spiking recurrent neural networks that match biological constraints of the cortex and are capable of performing cognitive tasks. An example of Dr. Sejnowski’s lab’s use of computational modeling, anatomical and biological parameters, and experimental data to elucidate neural mechanisms is his lab’s recent publication in The Journal of Neuroscience, “Feedforward Thalamocortical Connectivity Preserves Stimulus Timing Information in Sensory Pathways,” led by Hsi-Ping Wang and Jonathan W. Garcia.

Meaningful sensation and response to the visual world require timing precision and reliability of visual cortex activity. However, it remains incompletely understood how neurons in the primary visual cortex (V1) accomplish this, particularly considering variability of firing in earlier nuclei in the visual pathway, including the Lateral geniculate nucleus (LGN) in the thalamus. (The LGN receives input from retinal ganglion cells (RGC) and relays the visual information to spiny stellate neurons in layer four of V1.) To address this question, Wang et al. (2019) used previously published recordings from LGN neurons in cats (Kara et. al. 2000) as inputs to a Layer-4 spiny stellate cell model (Mainen and Sejnowski, 1998, Figure 1). This allowed them to vary parameters of LGN-V1 connectivity, including the number of LGN inputs, the number of synapses per afferent, and the total number of LGN synapse on the V1 neuron. They were then able to compare the output of the model, its spiking activity, to cat V1 cell spiking data recorded simultaneously to the LGN input by Kara et. al. (2000). Using this model, the authors demonstrated the effects of LGN input within and between trial variability on V1 neuron firing patterns. They found, among other things, that inter-trail variability of LGN firing reduced the reliability and precision of their model’s output, but increasing the number of LGN afferents and intra-trial variability restored reliability and timing precision. Through manipulating the LGN-V1 connectivity parameters of their model, they were able to recapitulate the experimental data and to confirm that the parameters used were consistent with observations from cat V1. This work revealed a novel mechanism by which cortical neurons in the mammalian visual cortex can maintain timing information about visual stimuli. This could provide insight into how thalamocortical inputs preserve stimulus timing information across sensory modalities. To learn more, check out Wang et. al. (2019).

wang et al fig 1

Figure 1. A. LGN spike trains recorded from an anesthetized cat by Kara et. al. (2000) in response to a drifting sinusoidal grating stimulus. Spike delivered as input to the V1 model. B, Modeled Cortical V1 Layer 4 Spiny Stellate system including LGN excitatory input, feedforward inhibition from interneurons, and background excitation and inhibition. Adapted from Wang et. al. 2019.

To hear more about Dr. Sejnowski’s approach and recent projects, join us at his talk titled “Lifelong adaptive learning, transfer and savings through gating in the prefrontal cortex” Tuesday April 14, 2020 at 4 pm via Zoom (

Written by Jennifer Jensen, a 1st year in the Neurosciences Graduate Program at UCSD.


Wang, H.-P., Garcia, J.W., Sabottke, C.F., Spencer, D.J., and Sejnowski, T.J. (2019) Feedforward thalamocortical connectivity preserves stimulus timing information in sensory pathways. J. Neurosci. 39: 7674–7688.

Kara P, Reinagel P, Reid RC (2000) Low response variability in simultaneously recorded retinal, thalamic, and cortical neurons. Neuron 27:635–646.

Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268:1503–1506.

Life in Color: Understanding Neural Processing of Multiple Types of Visual Information

What an amazing thing it is to see! Our brains are able to simultaneously process huge amounts of information taken in from our eyes in order to somehow give rise to conscious sight. Shape, edges, movement, depth, texture, and of course color must be properly integrated in order for us to experience what we know as vision. However, very few people can claim to have an in-depth knowledge of how our brains actually accomplish such a tremendous task. Neuroscientists studying the visual system have made it their lives’ work to understand how neural circuits in the visual system function in a way which allows us to perceive and interpret our surroundings.

One such scientist is Edward Callaway of the Salk Institute for Biological Studies. Callaway is a Fellow of The American Association for the Advancement of Science and of the American Academy of Arts and Sciences. He has spent his life using novel methods such as monosynaptic circuit tracing to understand the organization and function of the visual system. Recently, the Callaway lab published an article which revealed that color and orientation are coded in a way that differs from previously accepted models.

It was believed by some that color and orientation are retrieved separately from V1 and come to be represented by completely different cortical columns. These columns are thought to then project separately to higher order areas for additional processing. However, the Callaway lab demonstrates this is not the case.

Callaway and his team used a combinatorial approach of both drug-induced GCAMP6f expression, in vivo two-photon calcium imaging, and postmortem cytochrome oxidase staining to allow for the precise identification of cortical columns in relation to activity.


Fig. 1 In vivo GCaMp6f two-photon calcium imaging in primate V1.

(A) Schematic of experimental setup (see supplementary materials and methods). (B) Average fluorescence of one imaging region after presentation of colored drifting gratings. Four cells are indicated and their corresponding traces are shown in (C). Scale bar: 200 μm. (C) Sample fluorescence traces, indicated by the color of the stimulus to which they responded most strongly. Colored bars indicate the hue of the stimulus displayed at each time point. Adapted from “Color and orientation are jointly coded and spatially organized in primate primary visual cortex,” by E. Callaway, et al., 2019, Science, 1275-1279. Copyright [2020] by American Association for the Advancement of Science.

Anesthetized primates were shown drifting grafts at 12 specific color hues on a grey background while scientists recorded from V1 neurons. Neuron activity was measured using GCAMP6f, which causes changes in cellular fluorescence during calcium events (neuronal spiking). Neurons were then given both orientation selective index scores and color preference index scores based on how often cells fired in response to being shown specific colors or directionally moving shapes.

Researchers discovered a significant correlation between orientation selective index and color preference index scores, indicating a relationship between orientation and color tuning in V1 cells. Additionally, their findings show that of all visually responsive cells analyzed, 11.6 percent of them were both strongly orientation tuned and had a strong color preference. This directly contradicts previous models which suggest a strict separation or color and orientation processing and has predicted no such cells should exist.

These findings show that shape and color are both mutually extracted and represented amongst V1 neurons, and changes the way neuroscientists must think about information processing in the visual system. New models based off these findings will account for the presence of the cells demonstrated through this complex set of experiments.

Callaway will be giving a talk titled, “Functional Organization for Color Appearance Mechanisms in Primary Visual Cortex” on Tuesday, March 31st at 4PM. To watch live stream, click the following link: ZOOM:

Melonie Vaughn is a first year PhD student in Neuroscience currently rotating at the Autism Center of Excellence with Dr. Karen Pierce. 

Linking memories in time: what do hot chocolate and a bike have in common?

Whenever I drink hot chocolate I’m always reminded of the first time I rode a bike. Simply recalling the moment my dad let go of my bike as I was sent down my neighbor’s steep driveway unearths the snapshots of my mom making me hot chocolate in celebration and my dad taking off my training wheels. Our brain’s ability to encode and store memories is a popular subject of neuroscience research but little is known about how the brain is able to link these memories in time. A current theory called the memory allocation process hypothesizes that learning triggers a temporary increase in excitability, which biases the representation of one memory to share the neuronal ensemble representing a subsequent memory, allowing the recall of one memory to increase the likelihood of recalling another memory.

Dr. Denise Cai is an Assistant Professor of Neuroscience at Icahn School of Medicine at Mount Sinai studying temporal linking as well as memory capacity and sleep’s influence on memory. Studies in her lab involve how groups of neurons, or neuronal ensembles, in the brain represent contextual memories and how information shared between these neuronal ensembles can provide insight into how the brain sews together the snapshots of our lives to provide a temporal sequence for our memory.

A study published by Denise Cai et. al. titled “A shared neural ensemble links distinct contextual memories encoded close in time” aims to provide evidence for the memory allocation process and describe the mechanisms by which the brain links two distinct memories in time. Cai used in vivo calcium imaging with mini-microscopes of the CA1 region of the mouse hippocampus, a brain region known to be involved in memory, during exploration of three novel environments (Figure 1a-c). These environments (A, B, and C) represent three different contextual memories. Calcium imaging allows the group to observe which neurons are active during exploration of each distinct environment and if these environments are represented by different or similar neuronal ensembles. The mice were exposed to two of the contexts either 5 hours apart (B and C) or 7 days apart (A and C). The group observed that a larger number of neurons are shared between the representations of environments explored closer in time, environments A and B, than the contexts that were explored seven days apart, A and C (Fig 1d,f). Importantly, the group saw no significant difference in the number of active cells in each context, accounting for the possibility that the shared ensembles were influenced by a difference in the levels of activity in different environments (Fig 1e).

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Cai’s research provides evidence for the memory allocation process by showing that neurons activated by one context are also activated in a subsequent context, thereby supporting the notion that the activation of one neuronal ensemble can increase the likelihood of activation of another neuronal ensemble. The neurons that are shared between contexts could serve as the link between two memories shared close in time and provide a code for the sequencing of our memories that connect my first bike ride to a mug of hot chocolate.

To hear more about the work being done in Dr. Denise Cai’s lab, please join us at 4:00pm, Tuesday 03/10/2020 in the Marilyn G. Farquhar Seminar Room at the Center for Neural Circuits and Behavior.

____________________________________________________________________________________________  Kim Gagnon is a 1st year Neurosciences Ph.D. student currently rotating in Dr. Matthew Shtrahman’s lab studying the role of adult neurogenesis in memory formation and retrieval.




Targeting the Gut to Treat the Brain: The gut microbiome as a target in treatment of neurological disease

When we think of ourselves, our health and our behavior, most of us don’t often think of the trillions of bacteria, fungi and other microorganisms living inside of us. But researchers like Dr. Elaine Hsiao are showing us that we should. Our bodies have 10 times as many microorganism cells as human cells, and we are just beginning to understand the complexities of these microbial communities, collectively known as the microbiome, and to appreciate the profound effects they have on our bodies, brains and behavior, in health and disease. Research in Dr. Elaine Hsiao’s laboratory at the University of California Los Angeles is unraveling the effects and mechanisms of the microbiome-gut-brain axis and exploring how this knowledge can be used in the treatment of neurological diseases.

Given the great genetic and functional complexities of the microbiome, determining exactly how changes in the microbiome affect host development, physiology, and behavior and how we can use this knowledge to improve health is not a simple task. One approach that Dr. Hsiao and her team are taking to delineate the role of the gut microbiota in the treatment of neurological disease can be seen in the lab’s recent publication in Cell, led by Dr. Hsiao’s graduate student Christine Olson, “The Gut Microbiota Mediates the Anti-Seizure Effects of the Ketogenic Diet” (Olson et. al. 2018). In this paper, the authors manipulate the gut microbiome to establish that changes in gut microbiota composition are necessary and sufficient mediators of a dietary treatment in mouse models of refractory epilepsy. They then use metabolomics to guide the discovery of a molecular target sufficient to confer seizure protection, independent of diet.

A ketogenic diet, a diet that is high in fat and low in carbohydrates, is an effective treatment for refractory epilepsy (epilepsy that does not respond to current anticonvulsant medications), but it often fails because it is difficult for patients to maintain. The authors of this paper offer compelling evidence that the gut microbiome and its effects on host metabolism are important mediators of the seizure reducing effects of a ketogenic diet. They also show how this knowledge can be used to develop pharmacological alternatives. To do this, they first show that a ketogenic diet both reduces seizure susceptibility and changes the composition of the microbiome in two mouse models of refractory epilepsy. However, in germ free mice that lack a microbiome or in mice whose microbiome had been depleted by antibiotics, ketogenic diet did not reduce seizure susceptibility, suggesting that the microbiome is a necessary mediator of the effect. Furthermore, transferring either the fecal microbiota from mice on a ketogenic diet or only the species most greatly increased by the ketogenic diet (A. muciniphila, P. merdae, and P. distasonis) to germ-free mice, antibiotic treated mice, and  mice on control diet with intact microbiota reduced seizure susceptibility similarly to the ketogenetic diet, establishing sufficiency of changes in the microbiota composition to protect against seizure. The authors then used colonic, plasma and brain metabolomics to identify candidate mediators of the effect of the microbiome. Among their findings was a decrease in gamma-glutamylated amino acids in the colon and plasma in groups with reduced seizure susceptibility, suggesting that microbial communities that confer seizure resistance had reduced Gamma-Glutamyltranspeptidase (GGT) activity. To establish a link between this aspect of bacterial metabolism and seizure protection and to provide evidence that GGT activity may be an important pharmacological target for epilepsy treatment, they then treated mice with a GGT inhibitor. They indeed found that GTT inhibition was sufficient to confer seizure protection.

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Schematic of the findings in Olson et. al. 2018. Taken from Olson et. al. 2018.

Beyond advancing the understanding of a current epilepsy treatment and proposing a new pharmacological target for this devastating disease, this paper provides an excellent example of how Dr. Hsiao and her team are translating understanding the microbiome and its metabolism to meaningful insights about neurological development, disease and treatment.

To hear more about the work being done in Dr. Elaine Hsiao’s lab, please join us at 4:00pm, Tuesday 03/03/2020 in the Marilyn G. Farquhar Seminar Room at the Center for Neural Circuits and Behavior.

Written by Jennifer Jensen, a 1st year in the Neurosciences Graduate Program at UCSD currently working in Amir Zarrinpar’s Lab studying how engineered native bacteria can be used to manipulate the microbiome-gut-brain axis.


Olson, C.A., Vuong, H.E., Yano, J.M., Liang, Q.Y., Nusbaum D.J., Hsiao, E.Y. (2018) The gut microbiota mediates the anti-seizure effects of the ketogenic diet. Cell 173, 1728–1741.


Autism Spectrum Disorder: A Spectrum of Advances

Autism spectrum disorder (ASD) is a very complex and heterogeneous disease, commonly characterized with deficits in social communication, interaction, and repetitive patterns of behavior, interest and activities. Current pharmacological treatments can help with some of the medical and psychiatric comorbidities as well as symptom management, but none address the core deficit. Early diagnosis and intervention for ASD have been helpful in providing care so therefore, it is essential that we are able to identify children with ASD sooner.

Genetic risk accounts for around half of the causes of ASD, and within the last 30 years, over 100 genes have been identified to place children at risk for ASD. There are multiple co-occurring conditions in individuals with autism that can be used to create subgroups of this disorder. For example, 20-30% of individuals with autism have co-occurring epilepsy, gastrointestinal problems, or sleep disorders. These various subtypes make treatment for the core symptoms of ASD difficult and hard to identify. Dr. David G. Amaral heads the UC Davis MIND Institute Autism Phenome Project, which is a longitudinal, multidisciplinary analysis of over 400 families with children with autism. They collect an extensive amount of data to create clinically meaningful subtypes of ASD, making it eventually possible to have more customized treatment for each subtype. One recent subtype that Dr. Amaral’s lab has found is a neurophenotype that is characterized by megalencephaly, a brain size that is large and disproportionate to body size. Around 15% of boys with autism have this neurophenotype and children with autism and larger brains typically have been found to have more severe disabilities and poorer prognosis. More recently, Dr. Amaral’s lab has also found that ASD is associated with varied presentations of clinical anxiety as well. The standardized parent report anxiety scales done for children with ASD have reduced sensitivity to be able to detect clinical anxiety in ASD, especially for children with intellectual impairment.

On the other end of the spectrum, Dr. Amaral’s lab also has done extensive preclinical work looking into amygdala growth in the macque monkey. Evidence in the field has suggested that human amygdala growth coincides with complex socioemotional learning. This study was done to map the growth of a nonhuman primate amygdala from birth to adulthood using magnetic resonance images. As seen in the Figure 4 attachment from his paper, they discovered that the amygdala volume increases by 50% from age 6 months to 5 years, which is a longer period of growth than most other cortical gray and white matter. They suggest that because the amygdala grows for an extended period of time, there is more time for different deleterious environmental influences to affect this growth, potentially leading to multiple diseases where the amygdala is strongly implicated, including anxiety, depression, schizophrenia and autism.

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To hear more about the work being done in Dr. David G. Amaral ’s lab, please join us at 4:00pm, Tuesday 02/25/2020 in the Marilyn G. Farquhar Seminar Room at the Center for Neural Circuits and Behavior.


Written by Caroline Jia, a 1st year Neuroscience MSTP Student, working in Sung Han’s laboratory at the Salk Institute


5 More Minutes, said the Surgeon to the Anesthesiologist

Have you ever had that nightmare where you wake up in the middle of a surgery? Fortunately we have anesthesiologists to make sure that never happens. Anesthesia has been used for many years and in many forms, but remains very much an art form that relies on the skill and experience of the artist. The constant monitoring and delicate adjustments made by the anesthesiologist are absolutely crucial to a successful surgery with a fully unconscious patient! 

Aside from visually watching the patient for signs of consciousness, a very rough estimation, measures of brain states taken via electroencephalogram (EEG) are also used by the anesthesiologist. Raw EEG data is far too complicated to visually process and interpret in real time while also taking care of a patient, but there are commercial products that take this raw data and translate it into a single number from 0-100 that claims to measure depth of anesthesia. However, this single number is often inaccurate as it fails to take into account differences between individual patients and different types of anesthesia. A more personalized and informative metric is needed.

Dr. Emery Brown, M.D. Ph.D., is the Edward Hood Taplin Professor of Computational Neuroscience and Health Sciences & Technology at the Massachusetts Institute of Technology – and his group is working on just this problem. They are developing a system which uses the EEG signal of patients under anesthesia to automatically adjust the dosages. Specifically, they use a feature of EEG data called the power spectral density (PSD) which measures how much brain activity there is at different frequencies (the rate at which neurons are firing). For example, high power in 8-12 Hertz is known to correlate with relaxed but awake brain states. They further use a technique called Principal Component Analysis (PCA) to pull out just the relevant changes in PSD as a patient goes from conscious to unconscious. 

Importantly, this system starts with an estimation of sensitivity to anesthesia (based on an average patient) and then adjusts to match each particular patient. Furthermore, the system updates every 10 seconds to see if an adjustment to dosage is needed based on the above principal components. Further safety measures are included to prevent overdosing by restricting how much and how quickly doses can be increased. 

As for next steps, this system’s judgement needs to be tested against that of practicing anesthesiologists to validate that the decisions it is making are reasonable ones. However, a proven system like this has several benefits over the old methods: the constant monitoring and adjustment that does not require human action (freeing up the anesthesiologists for other relevant tasks), the automatic customization of the algorithms to the patient, the richness of information which is extracted from the EEG data, and the ability to easily include additional safety mechanisms. 

To hear more about the work being done in Dr. Brown’s lab, please join us at 4:00pm, Tuesday 02/11/2020 in the Marilyn G. Farquhar Seminar Room at the Center for Neural Circuits and Behavior.

This post written by Brianna Marsh, a first year in the UCSD Neurosciences Graduate Program interested in computational neuroscience and brain-computer-interfaces.

Sex differences in corticotropin releasing factor regulation

Whether it be acute or chronic, stress can disrupt our lives in many different ways. Although the previous sentence seems general, the concept of stress is considered broad within the field, with stress playing roles in many different diseases. While stress is not particularly understudied in neuroscience, the specific mechanisms and contributions our sex plays in regulation of stress hormones are. Currently, Dr. Debra Bangasser and her lab are trying to elucidate stress-induced deficits in hormone regulation and how that differs between males and females. Her lab employs a plethora of techniques, spanning across behavioral neuroscience and molecular biology to explore these differences.

In a recent publication from the Bangasser lab, they explored stress-induced deficits of medial septum-mediated memory formation utilizing rats as their model organism. They assert that, within the general population, males are more susceptible to cognitive impairments in neuropsychiatric disorders. Because of this, they hypothesized that corticotropin releasing factor (CRF) regulation differs between sex, and this difference may cause a deficit in memory formation.

They focused their attention to the medial septum (MS), which projects to the hippocampus, where they found that CRF in the MS impaired hippocampal-dependent object location memory in both sexes. In this novel object location task, rats are positioned in a box with objects that are placed in a specific layout. Then, after a time delay, rats are re-introduced to the box, but the layout of some objects within the box have changed. Rats spending a longer time with the familiar object versus the displaced object is considered a proxy for a deficit in spatial memory. In the figure below, both male and females had a deficit in the task with increasing amounts of CRF infused in the MS.


However, males were more sensitive than females to the CRF-induced task impairment. While this could be attributed to circulating ovarian hormones, they found that females have a higher expression of CRF binding protein in the MS, which keeps overall CRF bioavailability lower than males. Due to this difference, females are more resilient to these memory impairments.

Interestingly, they found that CRF antagonists prevented the memory impairments caused by CRF within the MS for both sexes. They claim that CRF antagonism may be a viable option for treatment of cognitive impairments in stressed individuals.

To hear more about the work being done in Dr. Debra Bangasser’s lab, please join us at 4:00pm, Tuesday 02/04/2020 in the Marilyn G. Farquhar Seminar Room at the Center for Neural Circuits and Behavior.

____________________________________________________________________________________________  Chiaki Santiago is a 1st year Neurosciences Ph.D. student currently rotating in Dr. Brenda Bloodgood’s lab. You can find her on Twitter and LinkedIn.