Panayiota Poirazi

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Panayiota Poirazi
Yiota2019.png
Born (1974-08-06) August 6, 1974 (age 49)
Cyprus
Alma materUniversity of Cyprus, Nicosia, Cyprus
University of Southern California, Los Angeles, California, USA
Known formodelling dendritic computations
Scientific career
FieldsNeuroscience, Computational Neuroscience
InstitutionsFoundation of Research and Technology-Hellas (FORTH), Institute of Molecular Biology and Biotechnology (IMBB)
Thesis Contributions of active dendrites and structural plasticity to the neural substrate for learning and memory  (2000)
Website http://www.dendrites.gr/

Panayiota Poirazi is a neuroscientist known for her work in modelling dendritic computations. She is an elected member of the European Molecular Biology Organization (EMBO).

Contents

Education and career

Poirazi studied at the University of Cyprus from 1992 until 1996. [1] She earned an M.S. from the University of Southern California in 1998, [2] and went on to earn her Ph.D. from there in 2000. [3] Following her Ph.D., she worked at the Alexander Fleming Instite of Immunology in Greece until 2001, when she moved to the Foundation for Research and Technology-Hellas (FORTH) in Crete, Greece in 2004. [1] As of 2021, she is the director of research at the Institute of Molecular Biology and Biotechnology (IMBB) at the Foundation for Research and Technology-Hellas (FORTH). [1]

Research

Poirazi is known for her work in neurobiology where she focuses on dendrites, the portion of a neuron that propagates signals. Her early research generated predictive models of how active dendrites and structural plasticity enhance storage capacity in single neurons. [4] She has used biophysical models of pyramidal neurons to show that dendrites of these cells integrate inputs in a sigmoidal manner, enabling the neurons to act as two-layer neural network devices. [5] [6] Poirazi has built a circuit-level model of the hippocampus that shows how memories are linked through time. [7] She has developed and applied biophysical models to explain how human neurons compute information, with a focus on solving the XOR problem. [8] [9]

Selected publications

Awards and honors

In 2017, Poirazi was elected a member of the European Molecular Biology Organization. [10] In 2018, she received a Friedrich Wilhelm Bessel Research Award from the Alexander von Humboldt Foundation. [11]

Related Research Articles

<span class="mw-page-title-main">Dendrite</span> Small projection on a neuron that receives signals

A dendrite or dendron is a branched protoplasmic extension of a nerve cell that propagates the electrochemical stimulation received from other neural cells to the cell body, or soma, of the neuron from which the dendrites project. Electrical stimulation is transmitted onto dendrites by upstream neurons via synapses which are located at various points throughout the dendritic tree.

<span class="mw-page-title-main">Neuropil</span> Type of area in the nervous system

Neuropil is any area in the nervous system composed of mostly unmyelinated axons, dendrites and glial cell processes that forms a synaptically dense region containing a relatively low number of cell bodies. The most prevalent anatomical region of neuropil is the brain which, although not completely composed of neuropil, does have the largest and highest synaptically concentrated areas of neuropil in the body. For example, the neocortex and olfactory bulb both contain neuropil.

<span class="mw-page-title-main">Dendritic spine</span> Small protrusion on a dendrite that receives input from a single axon

A dendritic spine is a small membranous protrusion from a neuron's dendrite that typically receives input from a single axon at the synapse. Dendritic spines serve as a storage site for synaptic strength and help transmit electrical signals to the neuron's cell body. Most spines have a bulbous head, and a thin neck that connects the head of the spine to the shaft of the dendrite. The dendrites of a single neuron can contain hundreds to thousands of spines. In addition to spines providing an anatomical substrate for memory storage and synaptic transmission, they may also serve to increase the number of possible contacts between neurons. It has also been suggested that changes in the activity of neurons have a positive effect on spine morphology.

<span class="mw-page-title-main">Long-term potentiation</span> Persistent strengthening of synapses based on recent patterns of activity

In neuroscience, long-term potentiation (LTP) is a persistent strengthening of synapses based on recent patterns of activity. These are patterns of synaptic activity that produce a long-lasting increase in signal transmission between two neurons. The opposite of LTP is long-term depression, which produces a long-lasting decrease in synaptic strength.

In neuroscience, synaptic plasticity is the ability of synapses to strengthen or weaken over time, in response to increases or decreases in their activity. Since memories are postulated to be represented by vastly interconnected neural circuits in the brain, synaptic plasticity is one of the important neurochemical foundations of learning and memory.

<span class="mw-page-title-main">Pyramidal cell</span> Projection neurons in the cerebral cortex and hippocampus

Pyramidal cells, or pyramidal neurons, are a type of multipolar neuron found in areas of the brain including the cerebral cortex, the hippocampus, and the amygdala. Pyramidal cells are the primary excitation units of the mammalian prefrontal cortex and the corticospinal tract. Pyramidal neurons are also one of two cell types where the characteristic sign, Negri bodies, are found in post-mortem rabies infection. Pyramidal neurons were first discovered and studied by Santiago Ramón y Cajal. Since then, studies on pyramidal neurons have focused on topics ranging from neuroplasticity to cognition.

<span class="mw-page-title-main">Barrel cortex</span> Region of the somatosensory cortex in some rodents and other species

The barrel cortex is a region of the somatosensory cortex that is identifiable in some species of rodents and species of at least two other orders and contains the barrel field. The 'barrels' of the barrel field are regions within cortical layer IV that are visibly darker when stained to reveal the presence of cytochrome c oxidase and are separated from each other by lighter areas called septa. These dark-staining regions are a major target for somatosensory inputs from the thalamus, and each barrel corresponds to a region of the body. Due to this distinctive cellular structure, organisation, and functional significance, the barrel cortex is a useful tool to understand cortical processing and has played an important role in neuroscience. The majority of what is known about corticothalamic processing comes from studying the barrel cortex, and researchers have intensively studied the barrel cortex as a model of neocortical column.

<span class="mw-page-title-main">Purkinje cell</span> Specialized neuron in the cerebellum

Purkinje cells, or Purkinje neurons, are a class of GABAergic inhibitory neurons located in the cerebellum. They are named after their discoverer, Czech anatomist Jan Evangelista Purkyně, who characterized the cells in 1839.

Schaffer collaterals are axon collaterals given off by CA3 pyramidal cells in the hippocampus. These collaterals project to area CA1 of the hippocampus and are an integral part of memory formation and the emotional network of the Papez circuit, and of the hippocampal trisynaptic loop. It is one of the most studied synapses in the world and named after the Hungarian anatomist-neurologist Károly Schaffer.

A basal dendrite is a dendrite that emerges from the base of a pyramidal cell that receives information from nearby neurons and passes it to the soma, or cell body. Due to their direct attachment to the cell body itself, basal dendrites are able to deliver strong depolarizing currents and therefore have a strong effect on action potential output in neurons. The physical characteristics of basal dendrites vary based on their location and species that they are found in. For example, the basal dendrites of humans are overall found to be the most intricate and spine-dense, as compared to other species such as Macaques. It is also observed that basal dendrites of the prefrontal cortex are larger and more complex in comparison to the smaller and simpler dendrites that can be seen within the visual cortex. Basal dendrites are capable of vast amounts of analog computing, which is responsible for many of the different nonlinear responses of modulating information in the neocortex. Basal dendrites additionally exist in dentate granule cells for a limited time before removal via regulatory factors. This removal usually occurs before the cell reaches adulthood, and is thought to be regulated through both intracellular and extracellular signals. Basal dendrites are part of the more overarching dendritic tree present on pyramidal neurons. They, along with apical dendrites, make up the part of the neuron that receives most of the electrical signaling. Basal dendrites have been found to be involved mostly in neocortical information processing.

Neural backpropagation is the phenomenon in which, after the action potential of a neuron creates a voltage spike down the axon, another impulse is generated from the soma and propagates towards the apical portions of the dendritic arbor or dendrites. In addition to active backpropagation of the action potential, there is also passive electrotonic spread. While there is ample evidence to prove the existence of backpropagating action potentials, the function of such action potentials and the extent to which they invade the most distal dendrites remain highly controversial.

Coincidence detection is a neuronal process in which a neural circuit encodes information by detecting the occurrence of temporally close but spatially distributed input signals. Coincidence detectors influence neuronal information processing by reducing temporal jitter and spontaneous activity, allowing the creation of variable associations between separate neural events in memory. The study of coincidence detectors has been crucial in neuroscience with regards to understanding the formation of computational maps in the brain.

Activity-dependent plasticity is a form of functional and structural neuroplasticity that arises from the use of cognitive functions and personal experience; hence, it is the biological basis for learning and the formation of new memories. Activity-dependent plasticity is a form of neuroplasticity that arises from intrinsic or endogenous activity, as opposed to forms of neuroplasticity that arise from extrinsic or exogenous factors, such as electrical brain stimulation- or drug-induced neuroplasticity. The brain's ability to remodel itself forms the basis of the brain's capacity to retain memories, improve motor function, and enhance comprehension and speech amongst other things. It is this trait to retain and form memories that is associated with neural plasticity and therefore many of the functions individuals perform on a daily basis. This plasticity occurs as a result of changes in gene expression which are triggered by signaling cascades that are activated by various signaling molecules during increased neuronal activity.

<span class="mw-page-title-main">Dendritic spike</span> Action potential generated in the dendrite of a neuron

In neurophysiology, a dendritic spike refers to an action potential generated in the dendrite of a neuron. Dendrites are branched extensions of a neuron. They receive electrical signals emitted from projecting neurons and transfer these signals to the cell body, or soma. Dendritic signaling has traditionally been viewed as a passive mode of electrical signaling. Unlike its axon counterpart which can generate signals through action potentials, dendrites were believed to only have the ability to propagate electrical signals by physical means: changes in conductance, length, cross sectional area, etc. However, the existence of dendritic spikes was proposed and demonstrated by W. Alden Spencer, Eric Kandel, Rodolfo Llinás and coworkers in the 1960s and a large body of evidence now makes it clear that dendrites are active neuronal structures. Dendrites contain voltage-gated ion channels giving them the ability to generate action potentials. Dendritic spikes have been recorded in numerous types of neurons in the brain and are thought to have great implications in neuronal communication, memory, and learning. They are one of the major factors in long-term potentiation.

<span class="mw-page-title-main">Nonsynaptic plasticity</span> Form of neuroplasticity

Nonsynaptic plasticity is a form of neuroplasticity that involves modification of ion channel function in the axon, dendrites, and cell body that results in specific changes in the integration of excitatory postsynaptic potentials and inhibitory postsynaptic potentials. Nonsynaptic plasticity is a modification of the intrinsic excitability of the neuron. It interacts with synaptic plasticity, but it is considered a separate entity from synaptic plasticity. Intrinsic modification of the electrical properties of neurons plays a role in many aspects of plasticity from homeostatic plasticity to learning and memory itself. Nonsynaptic plasticity affects synaptic integration, subthreshold propagation, spike generation, and other fundamental mechanisms of neurons at the cellular level. These individual neuronal alterations can result in changes in higher brain function, especially learning and memory. However, as an emerging field in neuroscience, much of the knowledge about nonsynaptic plasticity is uncertain and still requires further investigation to better define its role in brain function and behavior.

Synaptic tagging, or the synaptic tagging hypothesis, was first proposed in 1997 by Julietta U. Frey and Richard G. Morris; it seeks to explain how neural signaling at a particular synapse creates a target for subsequent plasticity-related product (PRP) trafficking essential for sustained LTP and LTD. Although the molecular identity of the tags remains unknown, it has been established that they form as a result of high or low frequency stimulation, interact with incoming PRPs, and have a limited lifespan.

Long-term potentiation (LTP), thought to be the cellular basis for learning and memory, involves a specific signal transmission process that underlies synaptic plasticity. Among the many mechanisms responsible for the maintenance of synaptic plasticity is the cadherin–catenin complex. By forming complexes with intracellular catenin proteins, neural cadherins (N-cadherins) serve as a link between synaptic activity and synaptic plasticity, and play important roles in the processes of learning and memory.

Addiction is a state characterized by compulsive engagement in rewarding stimuli, despite adverse consequences. The process of developing an addiction occurs through instrumental learning, which is otherwise known as operant conditioning.

<span class="mw-page-title-main">Michael Hausser</span>

Michael A. Häusser FRS FMedSci is professor of Neuroscience, based in the Wolfson Institute for Biomedical Research at University College London (UCL).

Rishikesh Narayanan is an Indian neuroscientist, computer engineer and a professor at the Molecular Biophysics Unit (MBU) of the Indian Institute of Science. He is the principal investigator at the Cellular Neurophysiology Laboratory of MBU where his team is engaged in researches on experimental and theoretical aspects of information processing in single neurons and their networks. The Council of Scientific and Industrial Research, the apex agency of the Government of India for scientific research, awarded him the Shanti Swarup Bhatnagar Prize for Science and Technology, one of the highest Indian science awards, in 2016, for his contributions to biological sciences.

References

  1. 1 2 3 "PANAYIOTA POIRAZI – FKNE" . Retrieved 2021-12-31.
  2. Poirazi, Panayiota (1998). Memory capacity of neurons with active dendrites (Thesis). OCLC   42188424.
  3. Poirazi, Panayiota (2000). Contributions of active dendrites and structural plasticity to the neural substrate for learning and memory (Thesis). OCLC   51873663.
  4. Poirazi, Panayiota; Mel, Bartlett W. (2001). "Impact of Active Dendrites and Structural Plasticity on the Memory Capacity of Neural Tissue". Neuron. 29 (3): 779–796. doi: 10.1016/S0896-6273(01)00252-5 . PMID   11301036. S2CID   14303314.
  5. Poirazi, Panayiota; Brannon, Terrence; Mel, Bartlett W. (March 2003). "Pyramidal Neuron as Two-Layer Neural Network". Neuron. 37 (6): 989–999. doi: 10.1016/s0896-6273(03)00149-1 . PMID   12670427. S2CID   1680778.
  6. Poirazi, Panayiota; Brannon, Terrence; Mel, Bartlett W. (2003-03-27). "Arithmetic of Subthreshold Synaptic Summation in a Model CA1 Pyramidal Cell". Neuron. 37 (6): 977–987. doi: 10.1016/S0896-6273(03)00148-X . ISSN   0896-6273. PMID   12670426. S2CID   15742277.
  7. Kastellakis, George; Silva, Alcino J.; Poirazi, Panayiota (2016-11-01). "Linking Memories across Time via Neuronal and Dendritic Overlaps in Model Neurons with Active Dendrites". Cell Reports. 17 (6): 1491–1504. doi:10.1016/j.celrep.2016.10.015. ISSN   2211-1247. PMC   5149530 . PMID   27806290.
  8. Gidon, Albert; Zolnik, Timothy Adam; Fidzinski, Pawel; Bolduan, Felix; Papoutsi, Athanasia; Poirazi, Panayiota; Holtkamp, Martin; Vida, Imre; Larkum, Matthew Evan (2020-01-03). "Dendritic action potentials and computation in human layer 2/3 cortical neurons". Science. 367 (6473): 83–87. Bibcode:2020Sci...367...83G. doi: 10.1126/science.aax6239 . PMID   31896716. S2CID   209676937.
  9. Cepelewicz, Jordana (2020-01-14). "Hidden Computational Power Found in the Arms of Neurons". Quanta Magazine. Retrieved 2021-12-31.
  10. "IMBB-FORTH's Researcher Panayiota Poirazi elected as member of EMBO". Foundation for Research and Technology - Hellas. June 16, 2017. Retrieved 2021-12-31.
  11. "Friedrich Wilhelm Bessel Research Award to IMBB researcher Panayiota Poirazi" (PDF). December 18, 2018. Retrieved December 31, 2021.