Anatomy
anatomy
Padraig Gleeson
The successful applicant will contribute to the goals of the OpenWorm project, to create a cell by cell model of the nematode C. elegans incorporating its full neuronal network and a 3D body/environment simulation. The role will involve contributing to existing and creating new software packages which facilitate the goals of the OpenWorm project. It will also involve carrying out research into the physiology, anatomy and behaviour of C. elegans, to ensure the simulations are biologically realistic. Code will be open source from the start and active interaction with the community of researchers in this area will be required.
Alberto Bacci
The successful candidate will work on inhibitory circuits of the prefrontal cortex of mice. In particular, they will study the properties and plasticity of synapses connecting a rich diversity of prefrontal cortical neuron subtypes. The candidate will also perform and analyze electrophysiological recordings in vivo, using high-density Neuropixels probes. This project is part of an ERA-Net NEURON international consortium and focuses on the rich diversity of GABAergic interneurons and their impact on the functional states of prefrontal cortical networks in healthy and diseased states.
Developmental and evolutionary perspectives on thalamic function
Brain organization and function is a complex topic. We are good at establishing correlates of perception and behavior across forebrain circuits, as well as manipulating activity in these circuits to affect behavior. However, we still lack good models for the large-scale organization and function of the forebrain. What are the contributions of the cortex, basal ganglia, and thalamus to behavior? In addressing these questions, we often ascribe function to each area as if it were an independent processing unit. However, we know from the anatomy that the cortex, basal ganglia, and thalamus, are massively interconnected in a large network. One way to generate insight into these questions is to consider the evolution and development of forebrain systems. In this talk, I will discuss the developmental and evolutionary (comparative anatomy) data on the thalamus, and how it fits within forebrain networks. I will address questions including, when did the thalamus appear in evolution, how is the thalamus organized across the vertebrate lineage, and how can the change in the organization of forebrain networks affect behavioral repertoires.
Cognitive maps as expectations learned across episodes – a model of the two dentate gyrus blades
How can the hippocampal system transition from episodic one-shot learning to a multi-shot learning regime and what is the utility of the resultant neural representations? This talk will explore the role of the dentate gyrus (DG) anatomy in this context. The canonical DG model suggests it performs pattern separation. More recent experimental results challenge this standard model, suggesting DG function is more complex and also supports the precise binding of objects and events to space and the integration of information across episodes. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG (the suprapyramidal blade vs the infrapyramidal blade). We propose a computational model that investigates this distinction. In the model the two processing streams (potentially localized in separate blades) contribute to the storage of distinct episodic memories, and the integration of information across episodes, respectively. The latter forms generalized expectations across episodes, eventually forming a cognitive map. We train the model with two data sets, MNIST and plausible entorhinal cortex inputs. The comparison between the two streams allows for the calculation of a prediction error, which can drive the storage of poorly predicted memories and the forgetting of well-predicted memories. We suggest that differential processing across the DG aids in the iterative construction of spatial cognitive maps to serve the generation of location-dependent expectations, while at the same time preserving episodic memory traces of idiosyncratic events.
Updating our models of the basal ganglia using advances in neuroanatomy and computational modeling
From primate anatomy to human neuroimaging: insights into the circuits underlying psychiatric disease and neuromodulation; Large-scale imaging of neural circuits: towards a microscopic human connectome
On Thursday, October 26th, we will host Anastasia Yendiki and Suzanne Haber. Anastasia Yendiki, PhD, is an Associate Professor in Radiology at the Harvard Medical School and an Associate Investigator at the Massachusetts General Hospital and Athinoula A. Martinos Center. Suzanne Haber, PhD, is a Professor at the University of Rochester and runs a lab at McLean hospital at Harvard Medical School in Boston. She has received numerous awards for her work on neuroanatomy. Beside her scientific presentation, she will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Location, time and type of epileptic activity influence how sleep modulates epilepsy
Sleep and epilepsy are tightly interconnected: On the one hand disturbed sleep is known to negatively affect epilepsy, whereas on the other hand epilepsy negatively impacts sleep. In this talk, we leverage on the unique opportunity provided by simultaneous stereo-EEG and sleep recordings to disentangle these relationships. We will discuss latest evidence on if anatomy (temporal vs. extratemporal), time (early vs. late sleep), and type of epileptic activity (ictal vs. interictal) influence how epileptic activity is modulated by sleep. After this talk, attendees will have a more nuanced understanding of the contributions of location, time and type of epileptic activity in the relationship between sleep and epilepsy.
Obesity and Brain – Bidirectional Influences
The regulation of body weight relies on homeostatic mechanisms that use a combination of internal signals and external cues to initiate and terminate food intake. Homeostasis depends on intricate communication between the body and the hypothalamus involving numerous neural and hormonal signals. However, there is growing evidence that higher-level cognitive function may also influence energy balance. For instance, research has shown that BMI is consistently linked to various brain, cognitive, and personality measures, implicating executive, reward, and attentional systems. Moreover, the rise in obesity rates over the past half-century is attributed to the affordability and widespread availability of highly processed foods, a phenomenon that contradicts the idea that food intake is solely regulated by homeostasis. I will suggest that prefrontal systems involved in value computation and motivation act to limit food overconsumption when food is scarce or expensive, but promote over-eating when food is abundant, an optimum strategy from an economic standpoint. I will review the genetic and neuroscience literature on the CNS control of body weight. I will present recent studies supporting a role of prefrontal systems in weight control. I will also present contradictory evidence showing that frontal executive and cognitive findings in obesity may be a consequence not a cause of increased hunger. Finally I will review the effects of obesity on brain anatomy and function. Chronic adiposity leads to cerebrovascular dysfunction, cortical thinning, and cognitive impairment. As the most common preventable risk factor for dementia, obesity poses a significant threat to brain health. I will conclude by reviewing evidence for treatment of obesity in adults to prevent brain disease.
Gut Feelings: The Microbiome as a Key Regulator of Brain & Behaviour Across the Lifespan
Building System Models of Brain-Like Visual Intelligence with Brain-Score
Research in the brain and cognitive sciences attempts to uncover the neural mechanisms underlying intelligent behavior in domains such as vision. Due to the complexities of brain processing, studies necessarily had to start with a narrow scope of experimental investigation and computational modeling. I argue that it is time for our field to take the next step: build system models that capture a range of visual intelligence behaviors along with the underlying neural mechanisms. To make progress on system models, we propose integrative benchmarking – integrating experimental results from many laboratories into suites of benchmarks that guide and constrain those models at multiple stages and scales. We show-case this approach by developing Brain-Score benchmark suites for neural (spike rates) and behavioral experiments in the primate visual ventral stream. By systematically evaluating a wide variety of model candidates, we not only identify models beginning to match a range of brain data (~50% explained variance), but also discover that models’ brain scores are predicted by their object categorization performance (up to 70% ImageNet accuracy). Using the integrative benchmarks, we develop improved state-of-the-art system models that more closely match shallow recurrent neuroanatomy and early visual processing to predict primate temporal processing and become more robust, and require fewer supervised synaptic updates. Taken together, these integrative benchmarks and system models are first steps to modeling the complexities of brain processing in an entire domain of intelligence.
Feedforward and feedback processes in visual recognition
Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, are now approaching – and sometimes even surpassing – human accuracy on a variety of visual recognition tasks. In this talk, however, I will show that these neural networks and their recent extensions exhibit a limited ability to solve seemingly simple visual reasoning problems involving incremental grouping, similarity, and spatial relation judgments. Our group has developed a recurrent network model of classical and extra-classical receptive field circuits that is constrained by the anatomy and physiology of the visual cortex. The model was shown to account for diverse visual illusions providing computational evidence for a novel canonical circuit that is shared across visual modalities. I will show that this computational neuroscience model can be turned into a modern end-to-end trainable deep recurrent network architecture that addresses some of the shortcomings exhibited by state-of-the-art feedforward networks for solving complex visual reasoning tasks. This suggests that neuroscience may contribute powerful new ideas and approaches to computer science and artificial intelligence.
What the fly’s eye tells the fly’s brain…and beyond
Fly Escape Behaviors: Flexible and Modular We have identified a set of escape maneuvers performed by a fly when confronted by a looming object. These escape responses can be divided into distinct behavioral modules. Some of the modules are very stereotyped, as when the fly rapidly extends its middle legs to jump off the ground. Other modules are more complex and require the fly to combine information about both the location of the threat and its own body posture. In response to an approaching object, a fly chooses some varying subset of these behaviors to perform. We would like to understand the neural process by which a fly chooses when to perform a given escape behavior. Beyond an appealing set of behaviors, this system has two other distinct advantages for probing neural circuitry. First, the fly will perform escape behaviors even when tethered such that its head is fixed and neural activity can be imaged or monitored using electrophysiology. Second, using Drosophila as an experimental animal makes available a rich suite of genetic tools to activate, silence, or image small numbers of cells potentially involved in the behaviors. Neural Circuits for Escape Until recently, visually induced escape responses have been considered a hardwired reflex in Drosophila. White-eyed flies with deficient visual pigment will perform a stereotyped middle-leg jump in response to a light-off stimulus, and this reflexive response is known to be coordinated by the well-studied giant fiber (GF) pathway. The GFs are a pair of electrically connected, large-diameter interneurons that traverse the cervical connective. A single GF spike results in a stereotyped pattern of muscle potentials on both sides of the body that extends the fly's middle pair of legs and starts the flight motor. Recently, we have found that a fly escaping a looming object displays many more behaviors than just leg extension. Most of these behaviors could not possibly be coordinated by the known anatomy of the GF pathway. Response to a looming threat thus appears to involve activation of numerous different neural pathways, which the fly may decide if and when to employ. Our goal is to identify the descending pathways involved in coordinating these escape behaviors as well as the central brain circuits, if any, that govern their activation. Automated Single-Fly Screening We have developed a new kind of high-throughput genetic screen to automatically capture fly escape sequences and quantify individual behaviors. We use this system to perform a high-throughput genetic silencing screen to identify cell types of interest. Automation permits analysis at the level of individual fly movements, while retaining the capacity to screen through thousands of GAL4 promoter lines. Single-fly behavioral analysis is essential to detect more subtle changes in behavior during the silencing screen, and thus to identify more specific components of the contributing circuits than previously possible when screening populations of flies. Our goal is to identify candidate neurons involved in coordination and choice of escape behaviors. Measuring Neural Activity During Behavior We use whole-cell patch-clamp electrophysiology to determine the functional roles of any identified candidate neurons. Flies perform escape behaviors even when their head and thorax are immobilized for physiological recording. This allows us to link a neuron's responses directly to an action.
The Standard Model of the Retina
The science of the retina has reached an interesting stage of completion. There exists now a consensus standard model of this neural system - at least in the minds of many researchers - that serves as a baseline against which to evaluate new claims. The standard model links phenomena from molecular biophysics, cell biology, neuroanatomy, synaptic physiology, circuit function, and visual psychophysics. It is further supported by a normative theory explaining what the purpose is of processing visual information this way. Most new reports of retinal phenomena fit squarely within the standard model, and major revisions seem increasingly unlikely. Given that our understanding of other brain circuits with comparable complexity is much more rudimentary, it is worth considering an example of what success looks like. In this talk I will summarize what I think are the ingredients that led to this mature understanding of the retina. Equally important, a number of practices and concepts that are currently en vogue in neuroscience were not needed or indeed counterproductive. I look forward to debating how these lessons might extend to other areas of brain research.
The evolution and development of visual complexity: insights from stomatopod visual anatomy, physiology, behavior, and molecules
Bioluminescence, which is rare on land, is extremely common in the deep sea, being found in 80% of the animals living between 200 and 1000 m. These animals rely on bioluminescence for communication, feeding, and/or defense, so the generation and detection of light is essential to their survival. Our present knowledge of this phenomenon has been limited due to the difficulty in bringing up live deep-sea animals to the surface, and the lack of proper techniques needed to study this complex system. However, new genomic techniques are now available, and a team with extensive experience in deep-sea biology, vision, and genomics has been assembled to lead this project. This project is aimed to study three questions 1) What are the evolutionary patterns of different types of bioluminescence in deep-sea shrimp? 2) How are deep-sea organisms’ eyes adapted to detect bioluminescence? 3) Can bioluminescent organs (called photophores) detect light in addition to emitting light? Findings from this study will provide valuable insight into a complex system vital to communication, defense, camouflage, and species recognition. This study will bring monumental contributions to the fields of deep sea and evolutionary biology, and immediately improve our understanding of bioluminescence and light detection in the marine environment. In addition to scientific advancement, this project will reach K-college aged students through the development and dissemination of educational tools, a series of molecular and organismal-based workshops, museum exhibits, public seminars, and biodiversity initiatives.
Human visual cortex as a window into the developing brain
Orbitofrontal cortex and the integrative approach to functional neuroanatomy
The project of functional neuroanatomy typically considers single brain areas as the core functional unit of the brain. Functional neuroanatomists typically use specialized tasks that are designed to isolate hypothesized functions from other cognitive processes. Our lab takes a broader view; specifically, we consider brain regions as parts of larger circuits and we take cognitive processes as part of more complex behavioral repertoires. In my talk, I will discuss the ramifications of this perspective for thinking about the role of the orbitofrontal cortex. I will discuss results of recent experiments from my lab that tackle the question of OFC function within the context of larger brain networks and in freely moving foraging tasks. I will argue that this perspective challenges conventional accounts of the role of OFC and invites new ones. I will conclude by speculating on implications for the practice of functional neuroanatomy.
Flexible motor sequence generation by thalamic control of cortical dynamics through low-rank connectivity perturbations
One of the fundamental functions of the brain is to flexibly plan and control movement production at different timescales to efficiently shape structured behaviors. I will present a model that clarifies how these complex computations could be performed in the mammalian brain, with an emphasis on the learning of an extendable library of autonomous motor motifs and the flexible stringing of these motifs in motor sequences. To build this model, we took advantage of the fact that the anatomy of the circuits involved is well known. Our results show how these architectural constraints lead to a principled understanding of how strategically positioned plastic connections located within motif-specific thalamocortical loops can interact with cortical dynamics that are shared across motifs to create an efficient form of modularity. This occurs because the cortical dynamics can be controlled by the activation of as few as one thalamic unit, which induces a low-rank perturbation of the cortical connectivity, and significantly expands the range of outputs that the network can produce. Finally, our results show that transitions between any motifs can be facilitated by a specific thalamic population that participates in preparing cortex for the execution of the next motif. Taken together, our model sheds light on the neural network mechanisms that can generate flexible sequencing of varied motor motifs.
What is the function of auditory cortex when it develops in the absence of acoustic input?
Cortical plasticity is the neural mechanism by which the cerebrum adapts itself to its environment, while at the same time making it vulnerable to impoverished sensory or developmental experiences. Like the visual system, auditory development passes through a series of sensitive periods in which circuits and connections are established and then refined by experience. Current research is expanding our understanding of cerebral processing and organization in the deaf. In the congenitally deaf, higher-order areas of "deaf" auditory cortex demonstrate significant crossmodal plasticity with neurons responding to visual and somatosensory stimuli. This crucial cerebral function results in compensatory plasticity. Not only can the remaining inputs reorganize to substitute for those lost, but this additional circuitry also confers enhanced abilities to the remaining systems. In this presentation we will review our present understanding of the structure and function of “deaf” auditory cortex using psychophysical, electrophysiological, and connectional anatomy approaches and consider how this knowledge informs our expectations of the capabilities of cochlear implants in the developing brain.
“From the Sublime to the Stomatopod: the story from beginning to nowhere near the end.”
“Call me a marine vision scientist. Some years ago - never mind how long precisely - having little or no money in my purse, and nothing particular to interest me on shore, I thought I would sail about a little and see what animals see in the watery part of the world. It is a way I have of dividing off the spectrum, and regulating circular polarisation.” Sometimes I wish I had just set out to harpoon a white whale as it would have been easier than studying stomatopod (mantis shrimp) vision. Nowhere near as much fun of course and certainly less dangerous so in this presentation I track the history of discovery and confusion that stomatopods deliver in trying to understand what the do actually see. The talk unashamedly borrows from that of Mike Bok a few weeks ago (April 13th 2021 “The Blurry Beginnings: etc” talk) as an introduction to the system (do go look at his talk again, it is beautiful!) and goes both backwards and forwards in time, trying to provide an explanation for the design of this visual system. The journey is again one of retinal anatomy and physiology, neuroanatomy, electrophysiology, behaviour and body ornaments but this time focusses more on polarisation vision (Mike covered the colour stuff well). There is a comparative section looking at the cephalopods too and by the end, I hope you will understand where we are at with trying to understand this extraordinary way of seeing the world and why we ‘pod-people’ wave our arms around so much when asked to explain; what do stomatopods see? Maybe, to butcher another quote: “mantis shrimp have been rendered visually beautiful for vision’s sake.”
Thalamocortical circuits from neuroanatomy to mental representations
In highly volatile environments, performing actions that address current needs and desires is an ongoing challenge for living organisms. For example, the predictive value of environmental signals needs to be updated when predicted and actual outcomes differ. Furthermore, organisms also need to gain control over the environment through actions that are expected to produce specific outcomes. The data to be presented will show that these processes are highly reliant on thalamocortical circuits wherein thalamic nuclei make a critical contribution to adaptive decision-making, challenging the view that the thalamus only acts as a relay station for the cortical stage. Over the past few years, our work has highlighted the specific contribution of multiple thalamic nuclei in the ability to update the predictive link between events or the causal link between actions and their outcomes via the combination of targeted thalamic interventions (lesion, chemogenetics, disconnections) with behavioral procedures rooted in experimental psychology. We argue that several features of thalamocortical architecture are consistent with a prominent role for thalamic nuclei in shaping mental representations.
BrainGlobe: a Python ecosystem for computational (neuro)anatomy
Neuroscientists routinely perform experiments aimed at recording or manipulating neural activity, uncovering physiological processes underlying brain function or elucidating aspects of brain anatomy. Understanding how the brain generates behaviour ultimately depends on merging the results of these experiments into a unified picture of brain anatomy and function. We present BrainGlobe, a new initiative aimed at developing common Python tools for computational neuroanatomy. These include cellfinder for fast, accurate cell detection in whole-brain microscopy images, brainreg for aligning images to a reference atlas, and brainrender for visualisation of anatomically registered data. These software packages are developed around the BrainGlobe Atlas API. This API provides a common Python interface to download and interact with reference brain atlases from multiple species (including human, mouse and larval zebrafish). This allows software to be developed agnostic to the atlas and species, increasing adoption and interoperability of software tools in neuroscience.
Neural dynamics underlying temporal inference
Animals possess the ability to effortlessly and precisely time their actions even though information received from the world is often ambiguous and is inadvertently transformed as it passes through the nervous system. With such uncertainty pervading through our nervous systems, we could expect that much of human and animal behavior relies on inference that incorporates an important additional source of information, prior knowledge of the environment. These concepts have long been studied under the framework of Bayesian inference with substantial corroboration over the last decade that human time perception is consistent with such models. We, however, know little about the neural mechanisms that enable Bayesian signatures to emerge in temporal perception. I will present our work on three facets of this problem, how Bayesian estimates are encoded in neural populations, how these estimates are used to generate time intervals, and how prior knowledge for these tasks is acquired and optimized by neural circuits. We trained monkeys to perform an interval reproduction task and found their behavior to be consistent with Bayesian inference. Using insights from electrophysiology and in silico models, we propose a mechanism by which cortical populations encode Bayesian estimates and utilize them to generate time intervals. Thereafter, I will present a circuit model for how temporal priors can be acquired by cerebellar machinery leading to estimates consistent with Bayesian theory. Based on electrophysiology and anatomy experiments in rodents, I will provide some support for this model. Overall, these findings attempt to bridge insights from normative frameworks of Bayesian inference with potential neural implementations for the acquisition, estimation, and production of timing behaviors.
Basal ganglia anatomy
Anatomical decision-making by cellular collectives: bioelectrical pattern memories, regeneration, and synthetic living organisms
A key question for basic biology and regenerative medicine concerns the way in which evolution exploits physics toward adaptive form and function. While genomes specify the molecular hardware of cells, what algorithms enable cellular collectives to reliably build specific, complex, target morphologies? Our lab studies the way in which all cells, not just neurons, communicate as electrical networks that enable scaling of single-cell properties into collective intelligences that solve problems in anatomical feature space. By learning to read, interpret, and write bioelectrical information in vivo, we have identified some novel controls of growth and form that enable incredible plasticity and robustness in anatomical homeostasis. In this talk, I will describe the fundamental knowledge gaps with respect to anatomical plasticity and pattern control beyond emergence, and discuss our efforts to understand large-scale morphological control circuits. I will show examples in embryogenesis, regeneration, cancer, and synthetic living machines. I will also discuss the implications of this work for not only regenerative medicine, but also for fundamental understanding of the origin of bodyplans and the relationship between genomes and functional anatomy.
Generalizing theories of cerebellum-like learning
Since the theories of Marr, Ito, and Albus, the cerebellum has provided an attractive well-characterized model system to investigate biological mechanisms of learning. In recent years, theories have been developed that provide a normative account for many features of the anatomy and function of cerebellar cortex and cerebellum-like systems, including the distribution of parallel fiber-Purkinje cell synaptic weights, the expansion in neuron number of the granule cell layer and their synaptic in-degree, and sparse coding by granule cells. Typically, these theories focus on the learning of random mappings between uncorrelated inputs and binary outputs, an assumption that may be reasonable for certain forms of associative conditioning but is also quite far from accounting for the important role the cerebellum plays in the control of smooth movements. I will discuss in-progress work with Marjorie Xie, Samuel Muscinelli, and Kameron Decker Harris generalizing these learning theories to correlated inputs and general classes of smooth input-output mappings. Our studies build on earlier work in theoretical neuroscience as well as recent advances in the kernel theory of wide neural networks. They illuminate the role of pre-expansion structures in processing input stimuli and the significance of sparse granule cell activity. If there is time, I will also discuss preliminary work with Jack Lindsey extending these theories beyond cerebellum-like structures to recurrent networks.
Cognition plus longevity equals culture: A new framework for understanding human brain evolution
Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.
Using marmosets for the study of the visual cortex: unique opportunities, and some pitfalls
Marmosets (Callithrix jacchus) are small South American monkeys which are being increasingly becoming adopted as animal models in neuroscience. Knowledge about the marmoset visual system has developed rapidly over the last decade. But what are the comparative advantages, and disadvantages involved in adopting this emerging model, as opposed to the more traditionally used macaque monkey? In this talk I will present case studies where the simpler brain morphology and short developmental cycle of the marmoset have been key factors in facilitating discoveries about the anatomy and physiology of the visual system. Although no single species provides the “ideal” animal model for invasive studies of the neural bases of visual processing, I argue that the development of robust methodologies for the study of the marmoset brain provides exciting opportunities to address long-standing problems in neuroscience.
Targeting Neural Plasticity by Optogenetic Silencing in the Auditory Cortex
Circuit mechanisms underlying the dynamic control of cortical processing by subcortical neuromodulators
Behavioral states such as arousal and attention can have profound effects on sensory processing, determining how – sometimes whether – a stimulus is processed. This state-dependence is believed to arise, at least in part, as a result of inputs to cortex from subcortical structures that release neuromodulators such as acetylcholine, noradrenaline, and serotonin, often non-synaptically. The mechanisms that underlie the interaction between these “wireless” non-synaptic signals and the “wired” cortical circuit are not well understood. Furthermore, neuromodulatory signaling is traditionally considered broad in its impact across cortex (within a species) and consistent in its form and function across species (at least in mammals). The work I will present approaches the challenge of understanding neuromodulatory action in the cortex from a number of angles: anatomy, physiology, pharmacology, and chemistry. The overarching goal of our effort is to elucidate the mechanisms behind local neuromodulation in the cortex of non-human primates, and to reveal differences in structure and function across cortical model systems.
Thalamocortical circuits from neuroanatomy to cognitive processes
Role of mechanical morphogenesis in the development and evolution of the cerebral cortex
The consequences and constraints of functional organization on behavior
In many ways, cognitive neuroscience is the attempt to use physiological observation to clarify the mechanisms that shape behavior. Over the past 25 years, fMRI has provided a system-wide and yet somewhat spatially precise view of the response in human cortex evoked by a wide variety of stimuli and task contexts. The current talk focuses on the other direction of inference; the implications of this observed functional organization for behavior. To begin, we must interrogate the methodological and empirical frameworks underlying our derivation of this organization, partially by exploring its relationship to and predictability from gross neuroanatomy. Next, across a series of studies, the implications of two properties of functional organization for behavior will be explored: 1) the co-localization of visual working memory and perceptual processing and 2) implicit learning in the context of distributed responses. In sum, these results highlight the limitations of our current approach and hint at a new general mechanism for explaining observed behavior in context with the neural substrate.
Neuroscience Investigations in the Virgin Lands of African Biodiversity
Africa is blessed with a rich diversity and abundance in rodent and avian populations. This natural endowment on the continent portends research opportunities to study unique anatomical profiles and investigate animal models that may confer better neural architecture to study neurodegenerative diseases, adult neurogenesis, stroke and stem cell therapies. To this end, African researchers are beginning to pay closer attention to some of her indigenous rodents and birds in an attempt to develop spontaneous laboratory models for homegrown neuroscience-based research. For this presentation, I will be showing studies in our lab, involving cellular neuroanatomy of two rodents, the African giant rat (AGR) and Greater cane rat (GCR), Eidolon Bats (EB) and also the Striped Owl (SO). Using histological stains (Cresyl violet and Rapid Golgi) and immunohistochemical biomarkers (GFAP, NeuN, CNPase, Iba-1, Collagen 2, Doublecortin, Ki67, Calbindin, etc), and Electron Microscopy, morphology and functional organizations of neuronal and glial populations of the AGR , GCR, EB and SO brains have been described, with our work ongoing. In addition, the developmental profiles of the prenatal GCR brains have been chronicled across its entire gestational period. Brains of embryos/foetuses were harvested for gross morphological descriptions and then processed using immunofluorescence biomarkers to determine the pattern, onset, duration and peak of neurogenesis (Pax6, Tbr1, Tbr2, NF, HuCD, MAP2) and the onset and peak of glial cell expressions and myelination in the prenatal GCR. The outcome of these research efforts has shown unique neuroanatomical expressions and networks amongst Africa’s rich biodiversity. It is hopeful that continuous effort in this regard will provide sufficient basic research data on neural developments and cellular neuroanatomy with subsequent translational consequences.
Predicting proprioceptive cortical anatomy and neural coding with topographic autoencoders
COSYNE 2023
Comparison of histological procedures and antigenicity of human postmortem brains fixed with solutions used in gross-anatomy laboratories
FENS Forum 2024
From anatomy to functions in locomotion: An optogenetic investigation on the organisation of V2a-derived reticulospinal neurons
FENS Forum 2024