The Life of the Cortical Column: Opening the Domain of Functional Architecture of the Cortex (1955–1981)
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An Investigation of the Cortical Learning Algorithm
Rowan University Rowan Digital Works Theses and Dissertations 5-24-2018 An investigation of the cortical learning algorithm Anthony C. Samaritano Rowan University Follow this and additional works at: https://rdw.rowan.edu/etd Part of the Electrical and Computer Engineering Commons, and the Neuroscience and Neurobiology Commons Recommended Citation Samaritano, Anthony C., "An investigation of the cortical learning algorithm" (2018). Theses and Dissertations. 2572. https://rdw.rowan.edu/etd/2572 This Thesis is brought to you for free and open access by Rowan Digital Works. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Rowan Digital Works. For more information, please contact [email protected]. AN INVESTIGATION OF THE CORTICAL LEARNING ALGORITHM by Anthony C. Samaritano A Thesis Submitted to the Department of Electrical and Computer Engineering College of Engineering In partial fulfillment of the requirement For the degree of Master of Science in Electrical and Computer Engineering at Rowan University November 2, 2016 Thesis Advisor: Robi Polikar, Ph.D. © 2018 Anthony C. Samaritano Acknowledgments I would like to express my sincerest gratitude and appreciation to Dr. Robi Polikar for his help, instruction, and patience throughout the development of this thesis and my research into cortical learning algorithms. Dr. Polikar took a risk by allowing me to follow my passion for neurobiologically inspired algorithms and explore this emerging category of cortical learning algorithms in the machine learning field. The skills and knowledge I acquired throughout my research have definitively molded me into a more diligent and thorough engineer. I have, and will continue to, take these characteristics and skills I have gained into my current and future professional endeavors. -
The Creation of Neuroscience
The Creation of Neuroscience The Society for Neuroscience and the Quest for Disciplinary Unity 1969-1995 Introduction rom the molecular biology of a single neuron to the breathtakingly complex circuitry of the entire human nervous system, our understanding of the brain and how it works has undergone radical F changes over the past century. These advances have brought us tantalizingly closer to genu- inely mechanistic and scientifically rigorous explanations of how the brain’s roughly 100 billion neurons, interacting through trillions of synaptic connections, function both as single units and as larger ensem- bles. The professional field of neuroscience, in keeping pace with these important scientific develop- ments, has dramatically reshaped the organization of biological sciences across the globe over the last 50 years. Much like physics during its dominant era in the 1950s and 1960s, neuroscience has become the leading scientific discipline with regard to funding, numbers of scientists, and numbers of trainees. Furthermore, neuroscience as fact, explanation, and myth has just as dramatically redrawn our cultural landscape and redefined how Western popular culture understands who we are as individuals. In the 1950s, especially in the United States, Freud and his successors stood at the center of all cultural expla- nations for psychological suffering. In the new millennium, we perceive such suffering as erupting no longer from a repressed unconscious but, instead, from a pathophysiology rooted in and caused by brain abnormalities and dysfunctions. Indeed, the normal as well as the pathological have become thoroughly neurobiological in the last several decades. In the process, entirely new vistas have opened up in fields ranging from neuroeconomics and neurophilosophy to consumer products, as exemplified by an entire line of soft drinks advertised as offering “neuro” benefits. -
An Abstract Model of a Cortical Hypercolumn
AN ABSTRACT MODEL OF A CORTICAL HYPERCOLUMN Baran Çürüklü1, Anders Lansner2 1Department of Computer Engineering, Mälardalen University, S-72123 Västerås, Sweden 2Department of Numerical Analysis and Computing Science, Royal Institute of Technology, S-100 44 Stockholm, Sweden ABSTRACT preferred stimulus was reported to be lower than to preferred stimulus. An abstract model of a cortical hypercolumn is presented. According to the findings by Hubel and Wiesel [16] This model could replicate experimental findings relating the primary visual cortex has a modular structure. It is to the orientation tuning mechanism in the primary visual composed of orientation minicolumns each one cortex. Properties of the orientation selective cells in the comprising some hundreds of pyramidal cells and a primary visual cortex like, contrast-invariance and smaller number of inhibitory interneurons of different response saturation were demonstrated in simulations. We kinds. Contrast edge orientation is coded such that the hypothesize that broadly tuned inhibition and local cells in each orientation minicolumn respond selectively excitatory connections are sufficient for achieving this to a quite broad interval of orientations. Further, the behavior. We have shown that the local intracortical orientation hypercolumn contains orientation minicolumns connectivity of the model is to some extent biologically with response properties distributed over all angles, and plausible. thus represents the local edge orientation pertinent to a given point in visual space. A similar modular arrangement is found in many other cortical areas, e.g. rodent whisker barrels [15]. 1. INTRODUCTION The Bayesian Confidence Propagation Neural Network model (BCPNN) has been developed in analogy Most neurons in the primary visual cortex (V1) with this possibly generic cortical structure [14]. -
A Detailed Model of the Primary Visual Pathway in The
The Journal of Neuroscience, July 1991, 7 7(7): 1959-l 979 A Detailed Model of the Primary Visual Pathway in the Cat: Comparison of Afferent Excitatory and lntracortical Inhibitory Connection Schemes for Orientation Selectivity Florentin WMg6tter” and Christof Koch Computation and Neural Systems Program, California Institute of Technology, Pasadena, California 91125 In order to arrive at a quantitative understanding of the dy- two inhibitory schemes, local and circular inhibition (a weak namics of cortical neuronal networks, we simulated a de- form of cross-orientation inhibition), is in good agreement tailed model of the primary visual pathway of the adult cat. with observed receptive field properties. The specificity re- This computer model comprises a 5”~ 5” patch of the visual quired to establish these connections during development field at a retinal eccentricity of 4.5” and includes 2048 ON- is low. We propose that orientation selectivity is caused by and OFF-center retinal B-ganglion cells, 8 192 geniculate at least three different mechanisms (“eclectic” model): a X-cells, and 4096 simple cells in layer IV in area 17. The weak afferent geniculate bias, broadly tuned cross-orien- neurons are implemented as improved integrate-and-fire tation inhibition, and some iso-orientation inhibition. units. Cortical receptive fields are determined by the pattern The most surprising finding is that an isotropic connection of afferent convergence and by inhibitory intracortical con- scheme, circular inhibition, in which a cell inhibits all of its nections. Orientation columns are implemented continuously postsynaptic target cells at a distance of approximately 500 with a realistic receptive field scatter and jitter in the pre- pm, enhances orientation tuning and leads to a significant ferred orientations. -
Torsten Wiesel (1924– ) [1]
Published on The Embryo Project Encyclopedia (https://embryo.asu.edu) Torsten Wiesel (1924– ) [1] By: Lienhard, Dina A. Keywords: vision [2] Torsten Nils Wiesel studied visual information processing and development in the US during the twentieth century. He performed multiple experiments on cats in which he sewed one of their eyes shut and monitored the response of the cat’s visual system after opening the sutured eye. For his work on visual processing, Wiesel received the Nobel Prize in Physiology or Medicine [3] in 1981 along with David Hubel and Roger Sperry. Wiesel determined the critical period during which the visual system of a mammal [4] develops and studied how impairment at that stage of development can cause permanent damage to the neural pathways of the eye, allowing later researchers and surgeons to study the treatment of congenital vision disorders. Wiesel was born on 3 June 1924 in Uppsala, Sweden, to Anna-Lisa Bentzer Wiesel and Fritz Wiesel as their fifth and youngest child. Wiesel’s mother stayed at home and raised their children. His father was the head of and chief psychiatrist at a mental institution, Beckomberga Hospital in Stockholm, Sweden, where the family lived. Wiesel described himself as lazy and playful during his childhood. He went to Whitlockska Samskolan, a coeducational private school in Stockholm, Sweden. At that time, Wiesel was interested in sports and became the president of his high school’s athletic association, which he described as his only achievement from his younger years. In 1941, at the age of seventeen, Wiesel enrolled at Karolinska Institutet (Royal Caroline Institute) in Solna, Sweden, where he pursued a medical degree and later pursued his own research. -
Probabilistic Skeletons Endow Brain-Like Neural Networks with Innate Computing Capabilities
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.18.444689; this version posted July 1, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Probabilistic skeletons endow brain-like neural networks with innate computing capabilities Christoph St¨ockl ∗1, Dominik Lang ∗1, and Wolfgang Maass 1 1Institute of Theoretical Computer Science, Graz University of Technology, Austria July 1, 2021 The genetic code endows neural networks of the brain with innate comput- ing capabilities. But it has remained unknown how it achieves this. Exper- imental data show that the genome encodes the architecture of neocortical circuits through pairwise connection probabilities for a fairly large set of ge- netically different types of neurons. We build a mathematical model for this style of indirect encoding, a probabilistic skeleton, and show that it suffices for programming a repertoire of quite demanding computing capabilities into neural networks. These computing capabilities emerge without learning, but are likely to provide a powerful platform for subsequent rapid learning. They are engraved into neural networks through architectural features on the sta- tistical level, rather than through synaptic weights. Hence they are specified in a much lower dimensional parameter space, thereby providing enhanced robustness and generalization capabilities as predicted by preceding work. 1 Introduction Artificial neural networks typically receive their computational capabilities through adap- tation of a very large set of parameters: through training of their synaptic weights with a very large number of examples, starting from a tabula rasa initial state. -
Cortical Layers: What Are They Good For? Neocortex
Cortical Layers: What are they good for? Neocortex L1 L2 L3 network input L4 computations L5 L6 Brodmann Map of Cortical Areas lateral medial 44 areas, numbered in order of samples taken from monkey brain Brodmann, 1908. Primary visual cortex lamination across species Balaram & Kaas 2014 Front Neuroanat Cortical lamination: not always a six-layered structure (archicortex) e.g. Piriform, entorhinal Larriva-Sahd 2010 Front Neuroanat Other layered structures in the brain Cerebellum Retina Complexity of connectivity in a cortical column • Paired-recordings and anatomical reconstructions generate statistics of cortical connectivity Lefort et al. 2009 Information flow in neocortical microcircuits Simplified version “computational Layer 2/3 layer” Layer 4 main output Layer 5 main input Layer 6 Thalamus e - excitatory, i - inhibitory Grillner et al TINS 2005 The canonical cortical circuit MAYBE …. DaCosta & Martin, 2010 Excitatory cell types across layers (rat S1 cortex) Canonical models do not capture the diversity of excitatory cell classes Oberlaender et al., Cereb Cortex. Oct 2012; 22(10): 2375–2391. Coding strategies of different cortical layers Sakata & Harris, Neuron 2010 Canonical models do not capture the diversity of firing rates and selectivities Why is the cortex layered? Do different layers have distinct functions? Is this the right question? Alternative view: • When thinking about layers, we should really be thinking about cell classes • A cells class may be defined by its input connectome and output projectome (and some other properties) • The job of different classes is to (i) make associations between different types of information available in each cortical column and/or (ii) route/gate different streams of information • Layers are convenient way of organising inputs and outputs of distinct cell classes Excitatory cell types across layers (rat S1 cortex) INTRATELENCEPHALIC (IT) | PYRAMIDAL TRACT (PT) | CORTICOTHALAMIC (CT) From Cereb Cortex. -
Medicine COVID-19 and RACISM
Columbia 2019–2020 ANNUAL REPORT Medicine Columbia University Vagelos College of Physicians & Surgeons FIGHTING TWO VIRUSES: COVID-19 AND RACISM Features: 4 12 20 At a Crossroads: All Hands on Deck The Bioethics of Medicine and Genomics and Justice the Movement Pivot was the action verb that describes how VP&S clinicians, A new ethics division is Work toward health equality researchers, and students expanding VP&S scholarship has begun at VP&S and all confronted COVID-19 when the into the ethical, legal, and of academic medicine as early virus arrived in New York City. social implications of precision summer protests revealed From redeploying clinicians to medicine. The 360-degree the health disparities in areas outside their specialty to perspective includes “studying medicine in general and graduating fourth-year students the studies” as researchers especially in COVID-19 cases. early, VP&S helped “bend the continue to unleash the Students and faculty share curve” at the epicenter of the power to treat, prevent, and their own perspectives on nation’s pandemic. cure disease. The effort also the intersection of COVID-19 provides an opportunity to and Black Lives Matter. bring social science to bear on bioethical questions. On the Cover Steven McDonald, MD, a 2014 VP&S graduate, is one of five faculty members and medical students who share their perspectives on the Black Lives Matter movement. Read about the five and the VP&S plans to promote racial justice, Page 4. Photograph by Jörg Meyer ColumbiaMedicine | 2019–2020 Annual Report Issue -
Scaling the Htm Spatial Pooler
International Journal of Artificial Intelligence and Applications (IJAIA), Vol.11, No.4, July 2020 SCALING THE HTM SPATIAL POOLER 1 2 1 1 Damir Dobric , Andreas Pech , Bogdan Ghita and Thomas Wennekers 1University of Plymouth, Faculty of Science and Engineering, UK 2Frankfurt University of Applied Sciences, Dept. of Computer Science and Engineering, Germany ABSTRACT The Hierarchical Temporal Memory Cortical Learning Algorithm (HTM CLA) is a theory and machine learning technology that aims to capture cortical algorithm of the neocortex. Inspired by the biological functioning of the neocortex, it provides a theoretical framework, which helps to better understand how the cortical algorithm inside of the brain might work. It organizes populations of neurons in column-like units, crossing several layers such that the units are connected into structures called regions (areas). Areas and columns are hierarchically organized and can further be connected into more complex networks, which implement higher cognitive capabilities like invariant representations. Columns inside of layers are specialized on learning of spatial patterns and sequences. This work targets specifically spatial pattern learning algorithm called Spatial Pooler. A complex topology and high number of neurons used in this algorithm, require more computing power than even a single machine with multiple cores or a GPUs could provide. This work aims to improve the HTM CLA Spatial Pooler by enabling it to run in the distributed environment on multiple physical machines by using the Actor Programming Model. The proposed model is based on a mathematical theory and computation model, which targets massive concurrency. Using this model drives different reasoning about concurrent execution and enables flexible distribution of parallel cortical computation logic across multiple physical nodes. -
From Controlling Elements to Transposons: Barbara Mcclintock and the Nobel Prize Nathaniel C
454 Forum TRENDS in Biochemical Sciences Vol.26 No.7 July 2001 Historical Perspective From controlling elements to transposons: Barbara McClintock and the Nobel Prize Nathaniel C. Comfort Why did it take so long for Barbara correspondence. From these and other to prevent her controlling elements from McClintock (Fig. 1) to win the Nobel Prize? materials, we can reconstruct the events moving because their effects were difficult In the mid-1940s, McClintock discovered leading up to the 1983 prize*. to study when they jumped around. She genetic transposition in maize. She What today are known as transposable never had any inclination to pursue the published her results over several years elements, McClintock called ‘controlling biochemistry of transposition. and, in 1951, gave a famous presentation elements’. During the years 1945–1946, at Current understanding of how gene at the Cold Spring Harbor Symposium, the Carnegie Dept of Genetics, Cold activity is regulated, of course, springs yet it took until 1983 for her to win a Nobel Spring Harbor, McClintock discovered a from the operon, François Jacob and Prize. The delay is widely attributed to a pair of genetic loci in maize that seemed to Jacques Monod’s 1960 model of a block of combination of gender bias and gendered trigger spontaneous and reversible structural genes under the control of an science. McClintock’s results were not mutations in what had been ordinary, adjacent set of regulatory genes (Fig. 2). accepted, the story goes, because women stable alleles. In the term of the day, they Though subsequent studies revealed in science are marginalized, because the made stable alleles into ‘mutable’ ones. -
Public Perceptions of S&T in Brazil, Funding Crisis and the Future
Public perceptions of S&T in Brazil, funding crisis and the future Interest in science and technology The interest in science and technology increased 15% in Brazil between the first and the more recent survey CGEE, 2015 Interest in science and technology European Union (2013) x Brazil (2015) 26% of the Brazilians are very interested in S&T, against 13% of the people interviewed in the European Union European Union 2013 Brazil 2015 Not interested Low interested Interested Very interested DK DA CGEE, 2015 Who is interested? DA DN Very interested Interested Not very interested Not interested Illiterate Elementary school Elementary High school University (incomplete) school (complete) degree (complete) CGEE, 2015 Those who have more formal education have more interest in S&T Do you remember... Do you know any Brazilian institution dedicated to scientific research? Do you remember the name of a Brazilian scientist? No Yes DA CGEE, 2015 50% of Brazilians think scientists are smart people who do useful things for humanity Science brings only benefits: 1987–12% 2006–29% 2010–38% 2015–54% What inspires the scientists? Helping humanity (34%), contributing to the advancement of knowledge (17%), contributing to the scientific and technological development of the country (15%) People in the government should follow guidelines developed by scientists Partially agree - 41% Completely agree - 18% Scientific and technological developments will lead to less social inequalities Partially agree - 35% Completely agree - 17% Considering the surveys... - People -
Universal Transition from Unstructured to Structured Neural Maps
Universal transition from unstructured to structured PNAS PLUS neural maps Marvin Weiganda,b,1, Fabio Sartoria,b,c, and Hermann Cuntza,b,d,1 aErnst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main D-60528, Germany; bFrankfurt Institute for Advanced Studies, Frankfurt/Main D-60438, Germany; cMax Planck Institute for Brain Research, Frankfurt/Main D-60438, Germany; and dFaculty of Biological Sciences, Goethe University, Frankfurt/Main D-60438, Germany Edited by Terrence J. Sejnowski, Salk Institute for Biological Studies, La Jolla, CA, and approved April 5, 2017 (received for review September 28, 2016) Neurons sharing similar features are often selectively connected contradictory to experimental observations (24, 25). Structured with a higher probability and should be located in close vicinity to maps in the visual cortex have been described in primates, carni- save wiring. Selective connectivity has, therefore, been proposed vores, and ungulates but are reported to be absent in rodents, to be the cause for spatial organization in cortical maps. In- which instead exhibit unstructured, seemingly random arrange- terestingly, orientation preference (OP) maps in the visual cortex ments commonly referred to as salt-and-pepper configurations are found in carnivores, ungulates, and primates but are not found (26–28). Phase transitions between an unstructured and a struc- in rodents, indicating fundamental differences in selective connec- tured map have been described in a variety of models as a function tivity that seem unexpected for closely related species. Here, we of various model parameters (12, 13). Still, the biological correlate investigate this finding by using multidimensional scaling to of the phase transition and therefore, the reason for the existence of predict the locations of neurons based on minimizing wiring costs structured and unstructured neural maps in closely related species for any given connectivity.