NT/ New connection between the eyes and touch discovered

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30 min readJul 10, 2020

Neuroscience biweekly vol. 10, 26th June — 10th July

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Latest researches

Oculomotor freezing reflects tactile temporal expectation and aids tactile perception

by Stephanie Badde, Caroline F. Myers, Shlomit Yuval-Greenberg, Marisa Carrasco in Nature Communications

Tiny eye movements can be used as an index of humans’ ability to anticipate relevant information in the environment independent of the information’s sensory modality, a team of scientists has found. The work reveals a connection between eye movements and the sense of touch.

“The fact that tiny eye movements can hinder our ability to discriminate tactile stimuli, and that the suppression of those eye movements before an anticipated tactile stimulus can enhance that same ability, may reflect that common brain areas, as well as common neural and cognitive resources, underlie both eye movements and the processing of tactile stimuli,” explains Marisa Carrasco, a professor of psychology and neural science at New York University and the senior author of the paper, which appears in the latest issue of the journal Nature Communications.

“This connection between the eyes and touch reveals a surprising link across perception, cognition, and action,” adds Stephanie Badde, an NYU post-doctoral researcher and first author of the paper.

The study asked human participants to distinguish between two kinds of vibrations (“fast” — high frequency vs. “slow” — low frequency) that were produced by a device connected to their finger. The researchers then tracked even the tiniest of their involuntary eye movements, known as micro-saccades. These small, rapid eye-movements are known to occur even when we try to fixate our gaze on one spot. Here, participants were instructed to focus their vision on a fixation spot on a computer screen. A cue — a tap elicited by the device at their finger — would announce the next imminent vibration. What the participants did not know is that the time interval between that cue and the tactile vibration was a central part of the experimental design.

The manipulation of that interval allowed participants in some blocks to predict with more accuracy precisely when the vibration would happen. Notably, when they had that precise information, the researchers could see not only how the participants’ microsaccade rates would decrease just before the vibration stimulus, but also how their ability to distinguish between fast and slow vibrations was enhanced by the suppression of micro-saccades.

a Setup. Participants sat at a table, their head supported by a chin and forehead rest, and fixated straight ahead while their eye position was monitored. Tactile stimulators were attached to the nondominant hand; the dominant hand rested on a keyboard. b Trial timeline. Trials began contingent on 0.5 s of continuous fixation, followed by a variable time interval of 0.2–0.7 s, ensuring that the stream of tactile stimuli within any block was nonrhythmic. Tactile cue and target were separated by a foreperiod of 1, 1.5, 2, 2.5, or 3 s. The cue was a single protruding movement of the stimulator tip; the target stimulus was a 50-ms-long vibration. Participants indicated by button press whether they perceived the target frequency as faster or slower than 60 Hz. c Design. We manipulated the degree of temporal predictability by either keeping the foreperiod (cue–target interval, blue ribbons) constant — regular condition — or variable — irregular condition — within blocks.

Synaptic plasticity induced by differential manipulation of tonic and phasic motoneurons in Drosophila

by Nicole A. Aponte-Santiago, Kiel G. Ormerod, Yulia Akbergenova, J. Troy Littleton in The Journal of Neuroscience

A new study by MIT neuroscientists into how seemingly similar neuronal subtypes drive locomotion in the fruit fly revealed an unexpected diversity as the brain’s commands were relayed to muscle fibers. A sequence of experiments revealed a dramatic difference between the two nerve cells — one neuron scrambled to adjust to different changes by the other, but received no requital in response when circumstances were reversed.

Structural and functional plasticity induced by neuronal competition is a common feature of developing nervous systems. However, the rules governing how postsynaptic cells differentiate between presynaptic inputs are unclear. In this study researchers characterized synaptic interactions following manipulations of tonic Ib or phasic Is glutamatergic motoneurons that co-innervate postsynaptic muscles of male or female Drosophila melanogaster larvae. After identifying drivers for each neuronal subtype, they performed ablation or genetic manipulations to alter neuronal activity and examined the effects on synaptic innervation and function at neuromuscular junctions (NMJs). Ablation of either Ib or Is resulted in decreased muscle response, with some functional compensation occurring in the Ib input when Is was missing. In contrast, the Is terminal failed to show functional or structural changes following loss of the co-innervating Ib input. Decreasing the activity of the Ib or Is neuron with tetanus toxin light chain resulted in structural changes in muscle innervation. Decreased Ib activity resulted in reduced active zone (AZ) number and decreased postsynaptic subsynaptic reticulum (SSR) volume, with the emergence of filopodial-like protrusions from synaptic boutons of the Ib input. Decreased Is activity did not induce structural changes at its own synapses, but the co-innervating Ib motoneuron increased the number of synaptic boutons and AZs it formed. These findings indicate tonic Ib and phasic Is motoneurons respond independently to changes in activity, with either functional or structural alterations in the Ib neuron occurring following ablation or reduced activity of the co-innervating Is input, respectively.

Food & mood: a review of supplementary prebiotic and probiotic interventions in the treatment of anxiety and depression in adults

by Sanjay Noonan, Meena Zaveri, Elaine Macaninch, Kathy Martyn in BMJ Nutrition, Prevention & Health

Probiotics either taken by themselves or when combined with prebiotics, may help to ease depression, suggests a review of the available evidence, published in BMJ Nutrition Prevention & Health.

Background A bidirectional relationship exists between the brain and the gastrointestinal tract. Foods containing bacteria that positively influence the gastrointestinal microbiome are termed, probiotics; compounds that promote the flourishing of these bacteria are termed, prebiotics. Whether microbiome influencing therapies could treat psychiatric conditions, including depression and anxiety, is an area of interest. Presently, no established consensus for such treatment exists.

Methods This systematic review analyses databases and grey literature sites to investigate pre and/or probiotics as treatments for depression and/or anxiety disorders. Articles included are from within 15 years. Pre-determined inclusion exclusion criteria were applied, and articles were appraised for their quality using a modified-CASP checklist. This review focuses specifically on quantitative measures from patients with clinical diagnoses of depression and/or anxiety disorders.

Results 7 studies were identified. All demonstrated significant improvements in one or more of the outcomes measuring the of effect taking pre/probiotics compared with no treatment/placebo, or when compared to baseline measurements.

An adapted PRISMA flowchart detailing search results acquired by actioning the strategy detailed in the Methods section. PRISMA, Preferred Reporting Items for Systematic Review and Meta-Analyses.

Discussion Thereview suggests utilising pre/probiotic may be a potentially useful adjunctive treatment. Furthermore, patients with certain co-morbidities, such as IBS, might experience greater benefits from such treatments, given that pre/probiotic are useful treatments for other conditions that were not the primary focus of this discourse. The results are limited by several factors: sample sizes (adequate, though not robust); short study durations, long-term effects and propensity for remission undetermined.

Conclusion The results affirm that pre/probiotic therapy warrants further investigation. Efforts should aim to elucidate whether the perceived efficacy of pre/probiotic therapy in depression and/or anxiety disorders can be replicated in larger test populations, and whether such effects are maintained through continued treatment, or post cessation. Interventions should also be investigated in isolation, not combination, to ascertain where the observed effects are attributable to. Efforts to produce mechanistic explanations for such effect should be a priority.

Cross-sectional and prospective relationship between occupational and leisure time inactivity and cognitive function in an ageing population

by Hayat, SA et al. in International Journal of Epidemiology

People who work in jobs that require less physical activity — typically office and desk-based jobs — are at a lower risk of subsequent poor cognition than those whose work is more physically active, suggests new research from the University of Cambridge.

Lack of physical activity and exercise are known risk factors for major health conditions, including cognitive impairments such as memory and concentration problems. However, evidence as to whether physical activity actually protects against cognitive decline has often been mixed and inconclusive.

Researchers examined patterns of physical activity among 8,500 men and women who were aged 40–79 years old at the start of the study and who had a wide range of socioeconomic backgrounds and educational attainment. The individuals were all part of the EPIC-Norfolk Cohort. In particular, the team were able to separate physical activity during work and leisure to see if these had different associations with later life cognition.

“The often used mantra ‘what is good for the heart, is good for the brain’ makes complete sense, but the evidence on what we need to do as individuals can be confusing,” said Shabina Hayat from the Department of Public Health and Primary Care at the University of Cambridge. “With our large cohort of volunteers, we were able to explore the relationship between different types of physical activity in a variety of settings.”

As part of the study, participants completed a health and lifestyle questionnaire, including information on the level of physical activity during both work and leisure, and underwent a health examination. After an average 12 years, the volunteers were invited back and completed a battery of tests that measured aspects of their cognition, including memory, attention, visual processing speed and a reading ability test that approximates IQ.

While many studies have only been able to report cross-sectional findings, the ability to follow up EPIC-Norfolk participants over a long period allowed the researchers to examine data prospectively. This helped them rule out any bias resulting from people with poor cognition — possibly as a result of cognitive impairment or early dementia — being less likely to be physically active due to poor cognition, rather than poor cognition being a result of physical inactivity.

Among their findings, published today in the International Journal of Epidemiology, the researchers report:

  • Individuals with no qualifications were more likely to have physically active jobs, but less likely to be physically active outside of work.
  • A physically inactive job (typically a desk-job), is associated with lower risk of poor cognition, irrespective of the level of education. Those who remained in this type of work throughout the study period were the most likely to be in the top 10% of performers.
  • Those in manual work had almost three times increased risk of poor cognition than those with an inactive job.

“Our analysis shows that the relationship between physical activity and cognitive is not straightforward,” explained Hayat. “While regular physical activity has considerable benefits for protection against many chronic diseases, other factors may influence its effect on future poor cognition.

“People who have less active jobs — typically office-based, desk jobs — performed better at cognitive tests regardless of their education. This suggests that because desk jobs tend to be more mentally challenging than manual occupations, they may offer protection against cognitive decline.”

It was not possible to say conclusively that physical activity in leisure time and desk-based work offer protection against cognitive decline. The researchers say that to answer this question, further studies will be required to include a more detailed exploration of the relationship of physical activity with cognition, particularly on inequalities across socio-economic groups and the impact of lower education.

Signal dynamics of midbrain dopamine neurons during economic decision-making in monkeys

by Mengxi Yun, Takashi Kawai, Masafumi Nejime, Hiroshi Yamada, Masayuki Matsumoto in Science Advances

Researchers have found that dopamine neurons in the brain can represent the decision-making process when making economic choices. As monkeys contemplated whether or not to choose an item, a subset of dopamine neurons transitioned from indicating the item’s value to indicating the monkey’s ultimate decision. Encoding of the decision into these dopamine neurons happened earlier than it did in other parts of the brain related to economic decision-making.

When we make economic choices, the brain first evaluates available options and then decides whether to choose them. Midbrain dopamine neurons are known to reinforce economic choices through their signal evoked by outcomes after decisions are made. However, although critical internal processing is executed while decisions are being made, little is known about the role of dopamine neurons during this period. Scientists found that dopamine neurons exhibited dynamically changing signals related to the internal processing while rhesus monkeys were making decisions. These neurons encoded the value of an option immediately after it was offered and then gradually changed their activity to represent the animal’s upcoming choice. Similar dynamics were observed in the orbitofrontal cortex, a center for economic decision-making, but the value-to-choice signal transition was completed earlier in dopamine neurons. The findings suggest that dopamine neurons are a key component of the neural network that makes choices from values during ongoing decision-making processes.

Economic decision-making task, monkeys’ behavior, and recording sites.

(A) Economic decision-making task. ITI, intertrial interval. (B) Choice rate of the first object in monkey A (n = 216 sessions) (left) and monkey E (n = 165 sessions) (right). (c )Rate of trials in which the monkey did not release the button within the second object presentation among trials in which the animal did not choose the first object. (D) Latency of the button release to choose the first object (circles) and to respond to the appearance of the second object (squares). Double asterisks indicate a significant difference between the latencies for the first and second objects (P < 0.01, two-tailed Wilcoxon signed-rank test). (E) Effects of the first (green) and second (orange) object values in the previous trial (t−1) and the first object value in the current trial (t) (purple) on the monkey’s choice. Double asterisks indicate a significant logistic regression coefficient (P < 0.01). Error bars in (B) to (E) indicate SEM, which are very small and hidden in most cases. (F and G) Recording sites shown on the images obtained by an MRI scan, in which the position of electrodes targeting the left SNc/VTA (red) (F) and the right OFC (yellow) (G) in monkey E is displayed.

Relationship between oxygen consumption and neuronal activity in a defined neural circuit

by Suzan Özugur, Lars Kunz, Hans Straka in BMC Biology

The brain has a high energy demand and reacts very sensitively to oxygen deficiency. Neurobiologists have now succeeded for the first time in directly correlating oxygen consumption with the activity of certain nerve cells.

The brain requires a disproportionate amount of energy compared to its body mass. This energy is mainly generated by aerobic metabolic processes that consume considerable amounts of oxygen. Therefore, the oxygen concentrations in the brain are an important parameter that influences the function of nerve cells and glial cells. However, how much oxygen is consumed in the brain and how this is related to neuronal activity was so far largely unknown. LMU neurobiologists Hans Straka, Suzan Özugur and Lars Kunz have now succeeded for the first time in directly measuring this in the intact brain and correlating it with nerve cell activity. The scientists report on their results in the journal BMC Biology.

In an already established animal model — tadpoles of the clawed frog Xenopus laevis — the scientists used electrochemical sensors to determine the concentration of oxygen in the brain and in one of the brain ventricles. They were able to specifically control the amount of oxygen available to the brain as well as inhibit nerve cell activity with the help of pharmacological substances. Using the example of nerve cells that control eye movements, the scientists succeeded in directly recording the relationship between oxygen consumption and nerve cell activity. “We have found that the brain is anoxic in a normal air-saturated environment, which means that no oxygen can be measured,” says Straka. The complete oxygen was therefore immediately used by the cells to synthesize energy-rich substances. If more than twice the atmospheric oxygen concentration was available, the energy metabolism was saturated and oxygen was abundantly present in the brain. “We were also able to show that during normal operation only about 50 percent of the oxygen is used for nerve cell activity,” says Straka. “So the other 50 percent are required for glial cells and for maintaining the basic metabolic rate of nerve cells. However, nerve cells with increased activity consume more oxygen.”

In order to better understand how information is processed in the brain, knowledge of the relationship between oxygen availability and brain activity is essential. The scientists’ results provide initial insight into this and are an important basis for further investigations of the brain’s energy balance in future experiments and for measuring oxygen consumption for various nerve cell functions. This could also be relevant from a medical point of view, for example to better understand the consequences of oxygen deficiency in the brain or to better interpret the information on brain activity obtained with imaging techniques.

Measurements of O2 levels in isolated preparations. a, b Photomicrograph, depicting an isolated head of a stage 53 tadpole (a1), a schematic transverse section of the hindbrain (a2), and a cross-sectioned head (b) at a rostro-caudal level indicated by the trapezoid in a1; red and blue circles and arrows in a2 indicate movements of the O2 electrode within the grid (white dots in b), used to construct the O2 profile (b). c Dual recordings of O2 concentrations in the bath and above the floor of the IVth ventricle in steps of 0.2 mm. d O2-concentration profile (mean ± SEM) of a midline depth track above the IVth ventricle (a2) in control (intact; color-coded) and metabolically inactive (EtOH-fixated; gray) preparations. e, f Recording of the ventricular O2 concentration in an EtOH-fixated preparation (e) during temporary increase of the bath O2 level to 650 μmol/l (gray area), and of an intact preparation (f) after bath-application of KCN (light pink area; 500 μmol/l); note that KCN causes an adjustment of the ventricular O2 level to the bath O2 level (single arrow in f) that remains matched (double arrow in f) when the bath O2 level is further increased (dark pink area). g Boxplot, depicting O2 concentrations in air-saturated bath solution (black), at the ventricular floor (red), and within the hindbrain (blue) in controls, in EtOH-fixated and KCN-treated preparations; note that EtOH-fixation and bath-application of KCN cause a significant increase of ventricular O2 concentrations to bath Ringer levels (***p < 0.0001; Mann-Whitney U test). h Scatter plot depicting coinciding ventricular and bath O2 levels in metabolically inactive (black dots, EtOH-fixated) or oxidative phosphorylation-impaired (pink dots, KCN) preparations. O2 levels in b–f are color-coded from blue (0 μmol/l) to red (300 μmol/l) to yellow (600 μmol/l); transverse hindbrain schemes indicate motion ( c)or position (e, f) of the O2 electrode. OT, optic tectum; R, rostral; C, caudal; SC, spinal cord; N, number of preparations

A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

by Ningfei Li, Juan Carlos Baldermann, Astrid Kibleur, Svenja Treu, Harith Akram, Gavin J. B. Elias, Alexandre Boutet, Andres M. Lozano, Bassam Al-Fatly, Bryan Strange, Juan A. Barcia, Ludvic Zrinzo, et al. in Nature Communications

A group of researchers from Charité — Universitätsmedizin Berlin have further refined the use of deep brain stimulation in the treatment of obsessive-compulsive disorder. By accurately localizing electrode placement in the brains of patients, the researchers were able to identify a fiber tract which is associated with the best clinical outcomes following deep brain stimulation. The researchers’ findings may be used to improve the treatment of obsessive-compulsive disorder.

A person with obsessive compulsive disorder (OCD) experiences unwanted thoughts and behaviors, the urge for which they find difficult or impossible to resist. More than 2 percent of people are affected by obsessive thoughts and compulsive behaviors which severely impair daily activities. A treatment option for severe cases is deep brain stimulation, a technique which is also used in other disorders, such as Parkinson’s disease. Deep brain stimulation involves the implantation of tiny electrodes into structures deep inside the brain. After implantation, these electrodes deliver very weak electric currents to help rebalance brain activity. By stimulating different areas of the brain, such as a fiber tract within the internal capsule or the subthalamic nucleus, this technique can help improve clinical symptoms in some cases. Treatment success depends on the accurate placement of electrodes and requires millimeter-level precision. The optimal stimulation target for patients with obsessive-compulsive disorders had not previously been identified.

For the first time, a team of researchers — led by Dr. Andreas Horn of Charité’s Department of Neurology with Experimental Neurology — has been able to identify a specific nerve bundle which appears to be the optimal target for stimulation. The researchers studied 50 patients with obsessive-compulsive disorder who received treatment at a number of centers around the world. Using magnetic resonance imaging technology both before and after electrode placement, the researchers were able to visualize surrounding fibre tracts and test to see which of these the electrodes were selectively stimulating. “Our analysis shows that optimal results are linked to a very specific nerve bundle. Reliable evidence for this link was found across the cohorts of patients examined in Cologne, Grenoble, London and Madrid,” explains Dr. Horn.

The researchers initially examined two cohorts of patients, both of which received deep brain stimulation to the internal capsule or the subthalamic nucleus. These brain structures have a variety of connections to other areas of the brain. And yet, a specific tract situated between the prefrontal cortex and the subthalamic nucleus was identified as a suitable target for stimulation in both of these groups. Precise electrode localizations allowed the researchers to reliably predict treatment outcomes in both of these groups. These results were then replicated in two further, independent cohorts. When comparing their results with other studies, the researchers showed that the target areas described were also located within the tract-target identified in this study.

Describing the way in which these findings could help with electrode implantation, the study’s first author, Ningfei Li, says: “Our results do not alter the original target area, they simply helped us to define it more precisely. What this means is that: so far, we have had to steer our boat toward an island which was shrouded in fog. Now, we can make out the island itself and perhaps even the pier, so we can aim for it with greater accuracy.” All 3D structural analysis data have been made publicly available to researchers around the world. No Charité patients with obsessive-compulsive disorder are receiving treatment using this invasive method of deep brain stimulation. However, the participating research centers continue to share their knowledge and are developing protocols for additional studies to test the newly defined target areas.

Overview of lead electrode placement. The two training/cross-validation cohorts (left) targeting ALIC (Cologne) and STN (Grenoble), and the two test cohorts (right) targeting NAcc (Madrid) and both ALIC & STN with four electrodes per patient (London) are shown. Subcortical structures defined by CIT-168 Reinforcement Learning Atlas63 (ALIC/NAcc region) and DISTAL Atlas (STN region), with coronal and axial planes of the T1-weighted ICMB 152 2009b nonlinear template as background.

Infectability of Human BrainSphere Neurons Suggests Neurotropism of SARS-CoV-2

by Bullen, C. K., Hogberg, H. T., Bahadirli-Talbott, A., Bishai, W. R., Hartung, T., Keuthan, C., Looney, M., Pekosz, A., Romero, J. C., Sillé, F., Um, P. and Smirnova, L. in ALTEX: Alternatives to Animal Experimentation.

A multidisciplinary team from two Johns Hopkins University institutions, including neurotoxicologists and virologists from the Bloomberg School of Public Health and infectious disease specialists from the school of medicine, has found that organoids (tiny tissue cultures made from human cells that simulate whole organs) known as “mini-brains” can be infected by the SARS-CoV-2 virus that causes COVID-19.

Early reports from Wuhan, China, the origin of the COVID-19 pandemic, have suggested that 36% of patients with the disease show neurological symptoms, but it has been unclear whether or not the virus infects human brain cells. In their study, the Johns Hopkins researchers demonstrated that certain human neurons express a receptor, ACE2, which is the same one that the SARS-CoV-2 virus uses to enter the lungs. Therefore, they surmised, ACE2 also might provide access to the brain.

When the researchers introduced SARS-CoV-2 virus particles into a human mini-brain model, the team found — for what is believed to be the first time — evidence of infection by and replication of the pathogen.

The human brain is well-shielded against many viruses, bacteria and chemical agents by the blood-brain barrier, which in turn, often prevents infections of the brain. “Whether or not the SARS-CoV-2 virus passes this barrier has yet to be shown,” notes senior author Thomas Hartung, M.D., Ph.D., chair for evidence-based toxicology at the Bloomberg School of Public Health. “However, it is known that severe inflammations, such as those observed in COVID-19 patients, make the barrier disintegrate.”

The impermeability of the blood-brain barrier, he adds, also can present a problem for drug developers targeting the brain.

The impact of SARS-CoV-2 on the developing brain is another concern raised by the study. Previous research from Paris-Saclay University has shown that the virus crosses the placenta, and embryos lack the blood-brain barrier during early development. “To be very clear,” Hartung says, “we have no evidence that the virus produces developmental disorders.”

However, the mini-brains — which model the growing human brain — contain the ACE2 receptor from their earliest stages of development. Therefore, Hartung says, the findings suggest that extra caution should be taken during pregnancy.

“This study is another important step in our understanding of how infection leads to symptoms, and where we might tackle the COVID-19 disease with drug treatment,” says William Bishai, M.D., Ph.D., professor of medicine at the Johns Hopkins University School of Medicine, and leader of the infectious disease team for the study.

The human stem cell-derived mini-brain models — known as BrainSpheres — were developed at the Bloomberg School of Public Health four years ago. They were the first mass-produced, highly standardized organoids of their kind, and have been used to model a number of diseases, including infections by viruses such as Zika, dengue and HIV.

Abnormal Development and Dysconnectivity of Distinct Thalamic Nuclei in Patients With 22q11.2 Deletion Syndrome Experiencing Auditory Hallucinations

by Valentina Mancini, Daniela Zöller, Maude Schneider, Marie Schaer, Stephan Eliez in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

A study reports that auditory hallucinations, a phenomenon in which people hear voices or other sounds, may arise through altered brain connectivity between sensory and cognitive processing areas.

Using magnetic resonance imaging (MRI), the researchers compared brain structures and their connectivity in 110 healthy control subjects and in 120 subjects with a genetic disorder, named 22q11.2 deletion syndrome, or DS. People with 22q11.2 DS are at far higher risk than the general public to develop schizophrenia and to experience sensory hallucinations. An estimated one percent of people with schizophrenia have this disorder.

Abnormalities in the thalamus, a brain region recognized as the “gateway” for sensory information coming into the brain, had already been implicated in schizophrenia and hallucinations. In the current study, the authors sought to parse more specifically how the thalamus and its connections to other brain areas differed in people with 22q11.2 DS — with and without auditory hallucinations (AH) — from the control group. For this longitudinal study, the researchers collected brain scans every three years from subjects aged 8 to 35, with each receiving between 1 and 4 scans.

While neither the total volume of the thalamus nor its developmental growth trajectory differed between 22q11.2 DS and control subjects, the researchers found differences in specific thalamic sub-nuclei. The medial and lateral geniculate nuclei (MGN, LGN), which are involved in relaying auditory and visual sensory information, were smaller in people with 22q11.2 DS. In contrast, thalamic nuclei that communicate with the frontal cortex, which is involved in higher cognitive functions, were larger in 22q11.2 DS subjects than in healthy controls. In addition, other thalamic nuclei developed differently in the two groups.

When comparing 22q11.2 DS subjects with and without AH, those with AH had a smaller volume of MGN and a different developmental trajectory.

Upon assessing functional connectivity within the brain, the authors also found that subjects with AH had greater connectivity between MGN with the auditory cortex and other language-processing areas. They postulate that such hyper-connectivity might underlie the activation of such auditory areas at rest, leading to hallucinations.

“These findings provide a mechanistic explanation to the extreme likelihood of hallucinatory phenomena in youths prone to psychosis due to 22q11.2 deletion syndrome,” Dr. Mancini added. “Further, the investigation of the developmental interactions between the thalamus and the cortex may help to identify new targets for intervention aimed at preventing the emergence of psychotic symptoms in individuals at-risk due to genetic conditions or clinical ultra-high-risk status.”

Comparison between patients with 22q11.2 deletion syndrome (22q11DS; in blue) and healthy control subjects (HC; in red). Mixed-model analysis of the developmental trajectories shows a marked smaller volume of the medial geniculate nucleus (MGN), lateral geniculate nucleus (LGN), pulvinar, and lateral posterior nucleus (LP) in patients with 22q11DS. Central panel: Example of thalamic segmentation in a deletion carrier (lower figures) and one healthy control (upper figures) showing the nuclei of interest in axial (a, d), coronal (b, e) and sagittal (c, f) sections. Volumes are expressed in mm3. L, left; PuA, anterior pulvinar; PuI, inferior putamen; PuL, lateral pulvinar; PuM, medial pulvinar; R, right; VA, ventral anterior; VLa, ventral lateral anterior; VLp, ventral lateral posterior; VPL, ventral posterolateral.

Real-time Inference and Detection of Disruptive EEG Networks for Epileptic Seizures

by Walter Bomela, Shuo Wang, Chun-An Chou, Jr-Shin Li in Scientific Reports

Research has shown that understanding brain activity as a network instead of readings from an EEG allow for more accurate and efficient detection of seizures in real-time.

Recent studies in brain science and neurological medicine paid a particular attention to develop machine learning-based techniques for the detection and prediction of epileptic seizures with electroencephalogram (EEG). As a noninvasive monitoring method to record brain electrical activities, EEG has been widely used for capturing the underlying dynamics of disruptive neuronal responses across the brain in real-time to provide clinical guidance in support of epileptic seizure treatments in practice. In this study, we introduce a novel dynamic learning method that first infers a time-varying network constituted by multivariate EEG signals, which represents the overall dynamics of the brain network, and subsequently quantifies its topological property using graph theory. Researchers demonstrate the efficacy of their learning method to detect relatively strong synchronization (characterized by the algebraic connectivity metric) caused by abnormal neuronal firing during a seizure onset. The computational results for a realistic scalp EEG database show a detection rate of 93.6% and a false positive rate of 0.16 per hour (FP/h); furthermore, the method observes potential pre-seizure phenomena in some cases.

Structure and flexibility in cortical representations of odour space

by Stan L. Pashkovski, Giuliano Iurilli, David Brann, Daniel Chicharro, Kristen Drummey, Kevin Franks, Stefano Panzeri, Sandeep Robert Datta in Nature

Neuroscientists describe for the first time how relationships between different odors are encoded in the brain. The findings suggest a mechanism that may explain why individuals have common but highly personalized experiences with smell, and inform efforts better understand how the brain transforms information about odor chemistry into the perception of smell.

Audiences and critics quickly concluded that the experience stunk. Fraught with technical issues, Smell-O-Vision was panned and became a running gag that holds a unique place in entertainment history. The flop of Smell-O-Vision, however, failed to deter entrepreneurs from continuing to chase the dream of delivering smells to consumers, particularly in recent years, through digital scent technologies. Such efforts have generated news headlines but scant success, due in part to a limited understanding of how the brain translates odor chemistry into perceptions of smell — a phenomenon that in many ways remains opaque to scientists.

A study by neurobiologists at Harvard Medical School now provides new insights into the mystery of scent. The researchers describe for the first time how relationships between different odors are encoded in the olfactory cortex, the region of brain responsible for processing smell.

By delivering odors with carefully selected molecular structures and analyzing neural activity in awake mice, the team showed that neuronal representations of smell in the cortex reflect chemical similarities between odors, thus enabling scents to be placed into categories by the brain. Moreover, these representations can be rewired by sensory experiences.

The findings suggest a neurobiological mechanism that may explain why individuals have common but highly personalized experiences with smell.

“All of us share a common frame of reference with smells. You and I both think lemon and lime smell similar and agree that they smell different from pizza, but until now, we didn’t know how the brain organizes that kind of information,” said senior study author Sandeep Robert Datta, associate professor of neurobiology in the Blavatnik Institute at HMS.

The results open new avenues of study to better understand how the brain transforms information about odor chemistry into the perception of smell.

“This is the first demonstration of how the olfactory cortex encodes information about the very thing that it’s responsible for, which is odor chemistry, the fundamental sensory cues of olfaction,” Datta said.

Computing odor

The sense of smell allows animals to identify the chemical nature of the world around them. Sensory neurons in the nose detect odor molecules and relay signals to the olfactory bulb, a structure in the forebrain where initial odor processing occurs. The olfactory bulb primarily transmits information to the piriform cortex, the main structure of the olfactory cortex, for more comprehensive processing.

Unlike light or sound, stimuli easily controlled by tweaking characteristics such as frequency and wavelength, it is difficult to probe how the brain builds neural representations of the small molecules that transmit odor. Often, subtle chemical changes — a few carbon atoms here or oxygen atoms there — can lead to significant differences in smell perception.

Datta, along with study first author Stan Pashkovski, research fellow in neurobiology at HMS, and colleagues approached this challenge by focusing on the question of how the brain identifies related but distinct odors.

“The fact that we all think a lemon and lime smell similar means that their chemical makeup must somehow evoke similar or related neural representations in our brains,” Datta said.

To investigate, the researchers developed an approach to quantitatively compare odor chemicals analogous to how differences in wavelength, for example, can be used to quantitatively compare colors of light. They used machine learning to look at thousands of chemical structures known to have odors and analyzed thousands of different features for each structure, such as the number of atoms, molecular weight, electrochemical properties and more. Together, these data allowed the researchers to systematically compute how similar or different any odor was relative to another. From this library, the team designed three sets of odors: a set with high diversity; one with intermediate diversity, with odors divided into related clusters; and one of low diversity, where structures varied only by incremental increases in carbon-chain length. They then exposed mice to various combinations of odors from the different sets and used multiphoton microscopy to image patterns of neural activity in the piriform cortex and olfactory bulb.

Smell prediction

The experiments revealed that similarities in odor chemistry were mirrored by similarities in neural activity. Related odors produced correlated neuronal patterns in both the piriform cortex and olfactory bulb, as measured by overlaps in neuron activity. Weakly related odors, by contrast, produced weakly related activity patterns. In the cortex, related odors led to more strongly clustered patterns of neural activity compared with patterns in the olfactory bulb. This observation held true across individual mice. Cortical representations of odor relationships were so well-correlated that they could be used to predict the identity of a held-out odor in one mouse based on measurements made in a different mouse.

Additional analyses identified a diverse array of chemical features, such as molecular weight and certain electrochemical properties, that were linked to patterns of neural activity. Information gleaned from these features was robust enough to predict cortical responses to an odor in one animal based on experiments with a separate set of odors in a different animal.

The researchers also found that these neural representations were flexible. Mice were repeatedly given a mixture of two odors, and over time, the corresponding neural patterns of these odors in the cortex became more strongly correlated. This occurred even when the two odors had dissimilar chemical structures. The ability of the cortex to adapt was generated in part by networks of neurons that selectively reshape odor relationships. When the normal activity of these networks was blocked, the cortex encoded smells more like the olfactory bulb.

“We presented two odors as if they’re from the same source and observed that the brain can rearrange itself to reflect passive olfactory experiences,” Datta said.

Part of the reason why things like lemon and lime smell alike, he added, is likely because animals of the same species have similar genomes and therefore similarities in smell perception. But each individual has personalized perceptions as well.

“The plasticity of the cortex may help explain why smell is on one hand invariant between individuals, and yet customizable depending on our unique experiences,” Datta said.

Together, the results of the study demonstrate for the first time how the brain encodes relationships between odors. In comparison to the relatively well-understood visual and auditory cortices, it is still unclear how the olfactory cortex converts information about odor chemistry into the perception of smell.

Identifying how the olfactory cortex maps similar odors now provides new insights that inform efforts to understand and potentially control the sense of smell, according to the authors.

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

by Markenscoff-Papadimitriou, E., Whalen, S., Przytycki, P., Thomas, R., Binyameen, F., Nowakowski, T. J., Kriegstein, A. R., Sanders, S. J., State, M. W., Pollard, K. S., & Rubenstein, J. L. in Cell

Researchers have created a comprehensive region-specific atlas of the regulatory regions of the genome linked to human embryonic brain development.

Researchers at Gladstone Institutes and UC San Francisco (UCSF) Weill Institute for Neurosciences have created a comprehensive region-specific atlas of the regulatory regions of the genome linked to human embryonic brain development.

“This gives us a searchable, data-rich atlas of part of the developing human brain,” said Katie Pollard, PhD, director of the Gladstone Institute of Data Science and Biotechnology. “This is a valuable tool for probing the underlying biology of neurodevelopmental disorders.”

Pollard and UCSF professor of psychiatry John Rubenstein are the senior authors of the new study, published online in the journal Cell.

Only about two percent of the human genome encodes actual genes. Much of the rest of the genome contains regulatory elements, the conductors that control when and where those genes are activated. Genes important for specific aspects of liver function, for example, don’t need to be turned on in brain cells, so different regulatory elements are needed to control gene expression in those tissues.

When researchers analyze the DNA of people with neurodevelopmental disorders, they often uncover dozens, if not hundreds, of natural variations in DNA sequences. However, only a minority of those variants may be related to the disorder itself, and pinning down which are important is difficult.

“Much of the genome is still this vast and mysterious place because we don’t know which parts of the genome play roles in which tissues,” said Eirene Markenscoff-Papadimitriou, PhD, a postdoctoral researcher at the UCSF Weill Institute for Neurosciences and co-first author of the paper.

In the new study, the researchers studied cells from a section of the developing human brain called the telencephalon. This region contains structures responsible for sensory processing, voluntary movement, language, and communication.

The team took advantage of the fact that inside cells, the genome is tightly wound into a dense structure known as chromatin. This three-dimensional structure reveals the important parts of the genome in any given cell by exposing the stretches of regulatory DNA needed for the cell to function. Using a technology called ATAC-seq, the team cut up exposed DNA in embryonic brain cells. By analyzing where these cuts are made, they were able to surmise what parts of the genome are exposed and might contain important regulatory regions.

Their initial experiments revealed more than 103,000 regions of open chromatin in the developing brain cells. To narrow down that list, the researchers turned to a machine-learning approach. They wrote a computer program that uses information already known about regulatory DNA to help pick out patterns specific to brain cells.

“We wanted to whittle this initial list down to a smaller set that was the most likely to be important to regulating brain development,” said Gladstone Research Scientist Sean Whalen, PhD, co-first author of the new paper.

If a regulatory region was similar to one known to only be active in limbs or lungs, for instance, the machine-learning program concluded that it wasn’t a brain-specific enhancer. In the end, the group came up with a set of about 19,000 regulatory regions of the genome expected to play a role in brain development.

To show the utility of the new dataset, the researchers looked more closely at two sections of the genome that appeared in the new atlas that had also been previously implicated in autism and epilepsy. The DNA sequences, they showed, did indeed act as enhancers in brain cells — they had the ability to turn on genes.

“We can now use this approach to ask how all sorts of other mutations affect the non-coding genome,” said Markenscoff-Papadimitriou. “This atlas points us in the direction of specific brain regions that are affected by genetic mutations.”

If a research team finds hundreds of genetic variants associated with a neurodevelopmental disease, for instance, they can now use the atlas to cross-check which variants are part of the 19,000 regions identified as critical to brain development. That can help them home in on which variants are worth follow-up studies, rather than spending months testing genetic variants that end up to be unrelated to disease.

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