Antagonism, Retinoic acid receptors

GO:0045202

GO synapse

GO:0010467

GO gene expression

MP:0002882

MP abnormal neuron morphology

GO:0007416

GO synapse assembly

GO:0099536

GO synaptic signaling

GO:0007612

GO learning

GO:0007613

GO memory

WIKI abnormal

WIKI decreased

WCS_9606

common toxicological species human

10116

NCBI rat

6239

NCBI Caenorhabditis elegans

10090

NCBI mouse

WCS_9606

common toxicological species humans

10095

NCBI mice

9685

NCBI cat

WCS_7227

common ecological species fruit fly

WCS_7955

common ecological species zebrafish

WCS_160004

common ecological species gastropods

Antagonism, Retinoic acid receptors

RAR antagonism

Molecular

AOPWiki 2024-06-06T12:28:11

2024-06-06T12:28:11

Altered, Gene Expression

Molecular

It is well documented that alterations of histone acetylation have an impact on gene expression. Therefore if the acetylation status of the epigenetic set-up at the regulatory sequences of genes is altered, this leads to changes in gene expression.

Gene specific alterations in histone acetylation at gene regulatory seqences can be measured by chromatin immunoprecipitation (ChIPs) and gene expression analysis by RT-qPCR or whole transcriptomics (RNAseq, gene chips).

CL:0000255

CL eukaryotic cell

AOPWiki 2016-11-29T18:41:31

2019-03-06T10:03:28

Decrease of GABAergic interneurons

GABAergic interneurons, Decreased

Cellular

Biological state The GABA-mediated depolarizing effects at the post-synaptic neurons in early development are well documented (Ben-Ari, 2014) and have been greatly correlated with the emergence of spontaneous network activity, which is the first neuronal activity of the brain (Voigt et al., 2001; Opitz et al., 2002). This spontaneous network activity is characterized by synchronous bursts of action potentials and concomitant intracellular calcium transients in large group of cells and it has been proposed to have functional role during the synaptogenesis and the formation of connections within the neuronal network (Wang and Kriegstein, 2010; Ben Ari et al., 2007; Blankenship and Feller, 2010). One of the milestones at the critical stage of brain development is the switch of the GABAergic signalling from depolarizing early in life to a more conventional hyperpolarizing inhibition on maturation (Ben-Ari et al., 2007). This developmental GABAergic switch is mainly driven by the expression change of the predominant potassium-chloride co-transporters (KCC2 and NKCC1) around this period that results in a shift from high to low intracellular Cl− concentration at the post-synaptic neurons (Lu et al., 1999). Biological compartments GABAergic interneurons are a heterogeneous group of neuronal cells that consist only of 10 to 20% of the total neuronal population (Aika et al., 1994; Halasy and Somogyi, 1993). They are characterized by aspiny dendrites and the release of GABA neurotransmitter, which makes them the main inhibitory source in the adult central nervous system (CNS) (Markram et al., 2004). A hallmark of interneurons is their structural and functional diversity. Many different subtypes have been identified in the cortex and hippocampus, but a global classification in specific categories is difficult to be established due to the variable morphological and functional properties (Klausberger and Somogyi, 2008; DeFelipe et al., 2013). The interneurons can be primarily identified by their characteristic morphology, which would divide them into 4 basic groups: basket cells, chandelier cells, bouquet cells and bitufted cells. However, a broader classification of these cells would require at least the following criteria: 1) morphology of soma, axonal and dendritic arbors; 2) molecular markers including but not restricted to calcium binding proteins (parvalbumin, calbindin, calretinin) and neuropeptides (e.g., Vasoactive Intestinal Peptide [VIP], reelin, somatostatin); 3) postsynaptic target cells; and 4) functional characteristics (Ascoli et al., 2008). They are neither motor nor sensory neurons, and also differ from projection neurons which send their signals to more distant locations. GABAergic interneurons are broadly present throughout the CNS, although telencephalic structures, such as the cerebral cortex and hippocampus, show the most abundant quantities of this neurotransmitter (Jones 1987). Complex interconnections between GABAergic interneurons and pyramidal cells shape the responses of pyramidal cells to incoming inputs, prevent runaway excitation, refine cortical receptive fields, and are involved in the timing and synchronisation of network oscillations (Wehr and Zador, 2003; Markram et al., 2004; LeMaqueresse and Monyer, 2013; Hu et al., 2014). General role in biology Inhibitory GABAergic interneurons of the adult nervous system play a vital role in neural circuitry and activity by regulating the firing rate of target neurons (reducing <a href="https://en.wikipedia.org/wiki/Neuron" title="Neuron">neuronal</a> excitability). In <a href="https://en.wikipedia.org/wiki/Vertebrates" title="Vertebrates">vertebrates</a>, GABA acts at inhibitory <a href="https://en.wikipedia.org/wiki/Chemical_synapse" title="Chemical synapse">synapses</a> in the <a href="https://en.wikipedia.org/wiki/Brain" title="Brain">brain</a> by binding to specific transmembrane <a href="https://en.wikipedia.org/wiki/Receptor_%28biochemistry%29" title="Receptor (biochemistry)">receptors</a> in the <a href="https://en.wikipedia.org/wiki/Plasma_membrane" title="Plasma membrane">plasma membrane</a> of both pre- and postsynaptic neuronal processes. Released neurotransmitter typically acts through postsynaptic GABAA ionotropic receptors in order to trigger a neuronal signalling pathway. This binding causes the opening of <a href="https://en.wikipedia.org/wiki/Ion_channel" title="Ion channel">ion channels</a> to allow the flow of either negatively charged <a href="https://en.wikipedia.org/wiki/Chloride" title="Chloride">chloride</a> ions into the <a href="https://en.wikipedia.org/wiki/Cell_%28biology%29" title="Cell (biology)">cell</a> or positively charged <a href="https://en.wikipedia.org/wiki/Potassium" title="Potassium">potassium</a> ions out of the cell. This action results in a negative change in the <a href="https://en.wikipedia.org/wiki/Transmembrane_potential" title="Transmembrane potential">transmembrane potential</a>, usually causing <a href="https://en.wikipedia.org/wiki/Hyperpolarization_%28biology%29" title="Hyperpolarization (biology)">hyperpolarization</a>. During early brain development GABA mediates depolarisation that has recently been shown to promote excitatory synapse formation by facilitating NMDA receptor activation in cortical pyramidal neurons (Wang and Kriegstein, 2008). GABAergic signalling has the unique property of "ionic plasticity", which is dependent on short-term and long-term concentration changes of Cl- and HCO3- in the postsynaptic neurons. The intracellular ion concentrations are largely modified in the course of brain development corresponding to the operation and functional modulation of ion transporters, such as the K-Cl co-transporter 2 (KCC2) and the Na-K-Cl co-transporter 1 (NKCC1) (Blaesse et al., 2009; Blankenship and Feller, 2010). GABA plays an important role as the first excitatory transmitter during embryogenesis and it has been shown to affect neurogenesis, differentiation, migration, and integration of developing neurons into neuronal circuits (LoTurco et al., 1995; Heck, et al., 2007). The effects of GABA being depolarizing are also important in the adult brain, as it has impact on synaptic plasticity and is strongly correlated with seizures (Baram and Hatalski, 1998; Ben-Ari et al., 2012). If GABAergic interneuron function breaks down, excitation takes over, leading to seizures and failure of higher brain functions (Westbrook, 2013)

Parvalbumin (PV) is a marker of  <a class="mw-redirect" href="https://en.wikipedia.org/wiki/GABA" title="GABA">GABAergic</a> <a href="https://en.wikipedia.org/wiki/Interneuron" title="Interneuron">interneurons</a> that can be identified by immunohistochemistry.  GABA or GAD can be used  for identification and morphometric analysis of the GABAergic neuronal population (Voigt et al., 2001; De Lima et al., 2007), with the use of anti-GABA antibodies. Protein levels on interneurons can be measured by commercial available antibody sandwich ELISA kits, Western blotting, immunohistochemistry and immunofluorescence and mRNA levels is possible to be measured with RT-PCR.  Calcium imaging experiments is the most common way to detect the depolarizing action of neurons, as this is correlated with a transient increase in intracellular calcium (Voigt et al., 2001). The local application of GABA agonist, muscimol, during the calcium imaging has been used the last decades in order to investigate the developmental effects of GABA in the post-synaptic neurons (Owens et al., 1996; Gangulu et al., 2001; Baltz et al., 2010; Westerholz et al., 2013).

Gamma-aminobutyric acid (GABA)ergic interneurons play a vital role in the wiring and circuitry of the developing nervous system of all organisms, both invertebrates and vertebrates (Hensch, 2005; Owens and Kriegstein, 2002; Wang et al., 2004). However, restricted expression of GABA in a considerable population of neurons is observed in the non-vertebrate animals. A nematode Caenorhabditis elegans has 302 neurons, among them, 26 cells are GABAergic (Sternberg and Horvitz, 1984; McIntire et al., 1993). Another nematode Ascaris has 26 GABAergic neurons (Obata, 2013). Glutamate decarboxylase (GAD), vesicular GABA transporter (VGAT), GABA receptors and GABA-system-specific molecules are analogous to those of vertebrates. Except for one interneuron, GABAergic neurons are connected with muscle cells and exert direct inhibitory, sometimes excitatory, control on locomotion, defecation and foraging. The muscle innervation of both excitatory and inhibitory axons is maintained also in Crustacea (Obata, 2013).

CL:0011005

CL GABAergic interneuron

High Mixed

High

During brain development

High High Low

Aika Y, Ren JQ, Kosaka K, Kosaka T. (1994). Quantitative analysis of GABA-like-immunoreactive and parvalbumin-containing neurons in the CA1 region of the rat hippocampus using a stereological method, the disector. Exp. Brain Res. 99: 267–276. Ascoli GA, Alonso-Nanclares L, Anderson SA, Barrionuevo G, Benavides-Piccione R, Burkhalter A, Buzsaki G, Cauli B, Defelipe J, Fairen A, et al. (2008). Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat. Rev. Neurosci. 9: 557–568. Baltz T, deLima AD, Voigt T. (2010). Contribution of GABAergic interneurons to the development of spontaneous activity patterns in cultured neocortical networks. Front. Cell Neurosci. 4:15. Baram TZ, Hatalski CG. (1998). Neuropeptide-mediated excitability: a key triggering mechanism for seizure generation in the developing brain. Trends Neurosci 21: 471–476. Ben-Ari Y, Gaiarsa JL, Tyzio R, Khazipov R. (2007). GABA: a pioneer transmitter that excites immature neurons and generates primitive oscillations. Physiol Rev 87:1215–84. Ben-Ari Y, Khalilov I, Kahle KT, Cherubini E. (2012). The GABA excitatory/inhibitory shift in brain maturation and neurological disorders. Neuroscientist 18:467–486. Ben-Ari. (2014). The GABA excitatory/inhibitory developmental sequence: a personal journey. Neuroscience 279:187–219. Blaesse P, Airaksinen MS, Rivera C, Kaila K. (2009). Cation chloride co-transporters and neuronal function. Neuron 61:820–838. Blankenship AG, Feller MB. (2010). Mechanisms underlying spon¬taneous patterned activity in develop¬ing neural circuits. Nat. Rev. Neurosci. 11:18–29. DeFelipe J, López-Cruz PL, Benavides-Piccione R, Bielza C, Larrañaga P, Anderson S et al. (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nat Rev Neurosci. 14: 202-216. deLima AD, Lima BD, Voigt T. (2007). Earliest spontaneous activity differentially regulates neocortical GABAergic interneuron subpopulations. Eur.J.Neurosci. 25: 1–16. Ganguly K, Schinder AF, Wong ST, Poo M. (2001). GABA itself promotes the developmental switch of neuronal GABAergic responses from excitation to inhibition. Cell 105:521–532. Halasy K, Somogyi P. (1993). Distribution of GABAergic synapses and their targets in the dentate gyrus of rat: A quantitative immunoelectron microscopic analysis. J. Hirnforsch. 34: 299–308. Heck N, Kilb W, Reiprich P et al. (2007). GABA-A receptors regulate neocortical neuronalmigration in vitro and in vivo. Cereb Cortex. 17:138–148. Hensch TK. (2005). Critical period plasticity in local cortical circuits. Nat Rev Neurosci. 6: 877-888. Hu H, Gan J, Jonas P. (2014). Interneurons. Fast-spiking, parvalbumin⁺ GABAergic interneurons: from cellular design to microcircuit function. Science. 345:1255-1263. Jones EG. (1987). GABA-peptide neurons in primate cerebral cortex. J Mind Behav 8:519–536. Klausberger T, Somogyi P. (2008). Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science. 321:53–57. Le Magueresse C, Monyer H. (2013). GABAergic interneurons shape the functional maturation of the cortex. Neuron. 77:388-405. LoTurco JJ, Owens DF, Heath MJS, Davis MBE, Kriegstein AR. (1995). GABA and glutamate depolarize cortical progenitor cells and inhibit DNA synthesis. Neuron. 15: 1287–1298. Lu J, Karadsheh M, Delpire E. (1999). Developmental regulation of the neuronal-specific isoform of K-Cl cotransporter KCC2 in postnatal rat brains. J Neurobiol 39: 558–568. Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. (2004). Interneurons of the neocortical inhibitory system. Nature Reviews Neuroscience, 5:793–807. McIntire SL, Jorgensen E, Kaplan J. and Horvitz, H.R. (1993) The GABAergic nervoussystem of Caenorhabditis elegans. Nature 364, 337–341. Obata K. (2013).Synaptic inhibition and gamma-aminobutyric acid in the mammalian central nervous system. Proc. Jpn. Acad., Ser. B 89 (2013). Opitz T, De Lima AD, Voigt T. (2002). Spontaneous development of synchronous oscillatory activity during maturation of cortical networks in vitro. J Neurophysiol 88:2196–2206. Owens DF, Boyce LH, Davis MBE, Kriegstein AR. (1996). Excitatory GABA responses in embryonic and neonatal cortical slices demonstrated by gramicidin perforated-patch recordings and calcium imaging. J Neurosci. 16: 6414–6423. Owens DF, Kriegstein AR. (2002). Is there more to GABA than synaptic inhibition? Nat Rev Neurosci 3:715-727. Sternberg PW. and Horvitz HR. (1984) The genetic control of cell lineage during nematode development. Annu. Rev. Genet. 18, 489–524. Voigt T, Opitz T, De Lima AD. (2001). Synchronous oscillatory activity in immature cortical network is driven by GABAergic preplate neurons. J Neurosci 21: 8895–8905. Wang DD, Kriegstein AR. (2008). GABA regulates excitatory synapse formation in the neocortex via NMDA receptor activation. J Neurosci. 28: 5547–5558. Wang DD, Kriegstein AR. (2010). Blocking early GABA depolarization with bumetanide results in permanent alterations in cortical circuits and sensorimotor gating deficits. Cereb Cortex 21:574–587. Wang XJ, Tegner J, Constantinidis C, Goldman-Rakic PS (2004). Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory. Proc Natl Acad Sci U S A. 101: 1368-1373. Wehr M, Zador AM. (2003). Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature. 426: 442–446. Westbrook G. (2013). “Seizures and epilepsy” in Principles of Neural Science, E. Kandel, J. H. Schwartz, T. M. Jessell, S. Siegelbaum, A. J. Hudspeth, Eds. McGraw-Hill, New York: 1116–1139. Westerholz S, de Lima AD, Voigt T. (2013). Thyroid hormone-dependent development of early cortical networks: temporal specificity and the contribution of trkB and mTOR pathways. Front Cell Neurosci 7: 121. AOPWiki 2016-11-29T18:41:27

2019-04-04T09:33:15

Decrease of synaptogenesis

Synaptogenesis, Decreased

Cellular

Biological state: Synaptogenesis is a multi-step process that is crucial for brain development and involves the formation of synapses. It follows axonal migration, at which stage presynaptic and postsynaptic differentiation occurs (Garner et al., 2002). "Synaptic assembly" that refers to the gathering of the appropriate components and "synaptic formation" that is defined by the mechanisms involved in recruitment of molecules required for differentiation, stabilization and maturation of synapse, are the main phases that characterise synaptogenesis (Colón-Ramos, 2009). Elimination is a physiological step involved in synaptogenesis regarding the synapses that fail to get stabilised and mature. The first step is the recognition and the establishment of contact between an axon and a dendritic spine in which pre- and postsynaptic neurons play important role. The presynaptic differentiation occurs followed by excretion of neurotransmitters that bind to appropriate receptors located on the target spine. However, a postsynaptic neuron does not passively receive guidance from a presynaptic axon but are the same dendritic filopodia that gradually are transformed into spines that select and engage their presynaptic neurons. The transformation of dendritic filopodia into dendritic spines that involves the expression of the whole postsynaptic machinery such as postsynaptic density (PSD), receptor subunits, scaffolding proteins and actin cytoskeleton, is the first step to give nascent synapses. However, to become functional and mature these synapses need an important number of cell-cell interactions, including stimulation from glutamatergic synapses as well as the influence of neurotrophic factors (Munno and Syed, 2003). However, all this is true for glutamatergic synapses because GABAergic synapses do not appear in dendritic spines, but rather form on dendritic shafts, nerve cell somata and axon initial segments. These inhibitory synapses besides their distinct location are also structurally different compared to excitatory synapses (reviewed in Gatto and Broadie, 2010). Biological compartments: Synaptogenesis is spatially and temporally strictly controlled process. It does not happen in a uniform way in all brain regions and there important differences between the times of appearance of the main two types of synapses (reviewed in Erecinska et al., 2004). For example, in rat hippocampus excitatory synapses are well established or fully mature within the two first postnatal weeks, whereas inhibitory synapses cannot be found prior to PND 18, after which it increases steadily to reach adult levels at PND 28. In addition, in rat neostriatal neurons the excitatory responses to both cortical and thalamic stimuli can be observed by PND 6, but the long-lasting hyperpolarization and late depolarization is never seen before PND 12. Structural remodelling of synapses and formation of new synaptic contacts has been postulated as a possible mechanism underlying the late phase of long-term potentiation (LTP), a form of plasticity which is involved in learning and memory. LTP induction results in a sequence of morphological changes consisting of a transient remodelling of the postsynaptic membrane followed by a marked increase in the proportion of axon terminals contacting two or more dendritic spines. Three-dimensional reconstruction revealed that these spines arose from the same dendrite. As pharmacological blockade of LTP prevented these morphological changes, it is suggested that LTP is associated with the formation of new, mature and probably functional synapses contacting the same presynaptic terminal and thereby duplicating activated synapses (Erik et al., 2006). In human, synaptogenesis does not happen at the same time in all brain regions, as the prefrontal cortex lags behind in terms of synapse formation compared to the auditory and visual cortices. In contrast, synaptogenesis appears to proceed concurrently in different brain areas for rhesus monkey (Erecinska et al., 2004). General role in biology: The period of rapid synaptogenesis or the so-called brain growth spurt is considered one of the most important processes that take place during brain development (Garner et al., 2002). This process is crucial not only in neurodevelopment but also plays a vital role in synaptic plasticity, learning and memory and adaptation throughout life. Without this process no complex brain network can be established as synapse is the fundamental unit of connectivity and communication between neurons (Tau and Peterson, 2010). Cell adhesion represents the most direct way of coordinating synaptic connectivity in the brain. Recent evidence highlights the importance of a trans-synaptic interaction between postsynaptic neuroligins and presynaptic neurexins. These transmembrane molecules bind each other extracellularly to promote adhesion between dendrites and axons, facilitating synapse establishment (Dean and Dresbach, 2006). Furthermore, the number of excitatory versus inhibitory synapses created at single neuron dictates neuronal excitability and function (Schummers et al., 2002).

Methods that have been previously reviewed and approved by a recognized authority should be included in the Overview section above. All other methods, including those well established in the published literature, should be described here. Consider the following criteria when describing each method: 1. Is the assay fit for purpose? 2. Is the assay directly or indirectly (i.e. a surrogate) related to a key event relevant to the final adverse effect in question? 3. Is the assay repeatable? 4. Is the assay reproducible? There is no OECD advised method for measuring synaptogenesis. Anatomical methods can be used to structurally estimate the number of excitatory or inhibitory synapses. Immunostaining can be employed with specific antibodies that recognize vesicular glutamate transporters (VGLUTs) and the postsynaptic density protein-95 kDa (PSD-95) that are characteristic of excitatory synapses, while inhibitory synapses are identified by the presence of the vesicular GABA (VGAT) and vesicular inhibitory amino acid (VIAAT) transporters and the postsynaptic adaptor protein gephryin (Gatto and Broadie, 2010). There are commercial available synaptogenesis assay kits that rely on the immunostaining of cells with MAP-2, PSD-95 and synaptophysin. Some other presynaptic (Bassoon) and postsynaptic (ProSAP1/Shank2) markers have been suggested and showed to correlate well with the ultrastructural studies in cultured hippocampus primary cells (Grabrucker et al., 2009). Electron microscopy can also be applied to assess the prevalence of excitatory and inhibitory synapses amongst convergent contacts (Megias et al., 2001). Recently, a high content image analysis based on RNAi screening protocols has been suggested as a useful tool to create imaging algorithm for use in both in vitro and in vivo synaptic punctae analysis (Nieland et al., 2014).

The mechanisms governing synapse formation is considered conserved among both vertebrates and invertebrates (Munno and Syed, 2003). Invertebrates have served as simple animal models to study synapse formation. Indeed, Colón-Ramos (2009) has recently reviewed the early developmental events that take place in the process of synaptogenesis pointing out the importance of this process in neural network formation and function. The experimental evaluation of synaptogenesis has been performed using invertebrates and in particular C. elegans and Drosophila as well as vertebrates (Colón-Ramos, 2009). This vulnerable period of synaptogenesis appears to happen in different developmental stages across species. For example, in rodents primarily synaptogenesis occurs during the first two weeks after birth (Bai et al., 2013). For rhesus monkeys, this period ranges from approximately 115-day gestation up to PND 60 (Bai et al., 2013). In humans, it starts from the third trimester of pregnancy and continues 2-3 years following birth (Bai et al., 2013).

CL:0000540

CL neuron

High Mixed

High

During brain development

High High High

Bai X, Twaroski D, Bosnjak ZJ. (2013) Modeling anesthetic developmental neurotoxicity using human stem cells. Semin Cardiothorac Vasc Anesth. 17: 276-287. Colón -Ramos DA. (2009) Synapse formation in developing neural circuits. Curr Top Devel Biol. 87: 53-79. Dean C, Dresbach T. (2006) Neuroligins and neurexins: linking cell adhesion, synapse formation and cognitive function. Trends Neurosci. 29:21-29. Erecinska M, Cherian S, Silver IA. (2004) Energy metabolism in mammalian brain during development. Prog Neurobiol. 73: 397-445. Erik I. Charyc, Barbara F. Akum, Joshua S. Goldber, Rebecka J. Jörnsten, Christopher Rongo, James Q. Zheng and Bonnie L. Firestein. Activity-Independent Regulation of Dendrite Patterning by Postsynaptic Density Protein PSD-95. Journal of Neuroscience 2006, 26(40): 10164-10176. Garner CC, Zhai RC, Gundelfinger ED, Ziv NE. (2002) Molecular mechanisms of CNS synaptogenesis. Cell Press 25: 243-250. Gatto CL, Broadie K. (2010) Genetic controls balancing excitatory and inhibitory synaptogenesis in neurodevelopmental disorder models. Front Syn Neurosci. 2: 4. Grabrucker A, Vaida B, Bockmann J, Boeckers TM. (2009) Synaptogenesis of hippocampal neurons in primary cell culture. Cell Tissue Res. 338: 333-341. Megias M, Emri Z, Freund TF, Gulyas AI. (2001) Total number and distribution of inhibitory and excitatory synapses on hippocampal CA1 pyramidal cells. Neuroscience 102: 527-540. Munno DW, Syed NI. (2003) Synaptogenesis in the CNS: an odyssey from wiring together to firing together. J Physiol. 552: 1-11. Nieland TJF, Logan DJ, Saulnier J, Lam D, Johnson C, et al. (2014) High Content Image Analysis Identifies Novel Regulators of Synaptogenesis in a High-Throughput RNAi Screen of Primary Neurons. PLoS ONE. 9: e91744. Schummers J, Mariño J, Sur M. (2002) Synaptic integration by V1 neurons depends on location within the orientation map. Neuron. 36: 969-978. Tau GZ, Peterson BS. (2010) Normal Development of Brain Circuits. Neuropsychopharmacology 35: 147-168. AOPWiki 2016-11-29T18:41:24

2017-09-16T10:14:27

Decrease of neuronal network function

Neuronal network function, Decreased

Organ

Biological state: There are striking differences in neuronal network formation and function among the developing and mature brain. The developing brain shows a slow maturation and a transient passage from spontaneous, long-duration action potentials to synaptically-triggered, short-duration action potentials. Furthermore, at this precise developmental stage the neuronal network is characterised by "hyperexcitability”, which is related to the increased number of local circuit recurrent excitatory synapses and the lack of γ-amino-butyric acid A (GABAA)-mediated inhibitory function that appears much later. This “hyperexcitability” disappears with maturation when pairing of the pre- and postsynaptic partners occurs and synapses are formed generating population of postsynaptic potentials and population of spikes followed by developmental GABA switch. Glutamatergic neurotransmission is dominant at early stages of development and NMDA receptor-mediated synaptic currents are far more times longer than those in maturation, allowing more calcium to enter the neurons. The processes that are involved in increased calcium influx and the subsequent intracellular events seem to play a critical role in establishment of wiring of neural circuits and strengthening of synaptic connections during development (reviewed in Erecinska et al., 2004). Neurons that do not receive glutaminergic stimulation are undergoing developmental apoptosis. During the neonatal period, the brain is subject to profound alterations in neuronal circuitry due to high levels of synaptogenesis and gliogenesis. For example, in neuroendocrine regions such as the preoptic area-anterior hypothalamus (POA-AH), the site of gonadotropin-releasing hormone (GnRH) system is developmentally regulated by glutamatergic neurons. The changes in the expression of the N-methyl-D-aspartate (NMDA) receptor subunits NR1 and NR2B system begin early in postnatal development, before the onset of puberty, thereby playing a role in establishing the appropriate environment for the subsequent maturation of GnRH neurons (Adams et al., 1999). Biological compartments: Neural network formation and function happen in all brain regions but it appears to onset at different time points of development (reviewed in Erecinska et al., 2004). Glutamatergic neurotransmission in hippocampus is poorly developed at birth. Initially, NMDA receptors play important role but the vast majority of these premature glutamatergic synapses are “silent” possibly due to delayed development of hippocampal AMPA receptors. In contrast, in the cerebral cortex the maturation of excitatory glutamatergic neurotransmission happens much earlier. The “silent” synapses disappear by PND 7-8 in both brain regions mentioned above. There is strong evidence suggesting that NMDA receptor subunit composition controls synaptogenesis and synapse stabilization (Gambrill and Barria, 2011). It is established fact that during early postnatal development in the rat hippocampus, synaptogenesis occurs in parallel with a developmental switch in the subunit composition of NMDA receptors from NR2B to NR2A. It is suggested that early expression of NR2A in organotypic hippocampal slices reduces the number of synapses and the volume and dynamics of spines. In contrast, overexpression of NR2B does not affect the normal number and growth of synapses. However, it does increase spine motility, adding and retracting spines at a higher rate. The C terminus of NR2B, and specifically its ability to bind CaMKII, is sufficient to allow proper synapse formation and maturation. Conversely, the C terminus of NR2A was sufficient to stop the development of synapse number and spine growth. These results indicate that the ratio of synaptic NR2B over NR2A controls spine motility and synaptogenesis, and suggest a structural role for the intracellular C terminus of NR2 in recruiting the signalling and scaffolding molecules necessary for proper synaptogenesis. Interestingly, it was found that genetic deletion of NR3A accelerates glutamatergic synaptic transmission, as measured by AMPAR-mediated postsynaptic currents recorded in hippocampal CA1. Consistent, the deletion of NR3A accelerates the expression of the glutamate receptor subunits NR1, NR2A, and GluR1 sugesting that glutamatergic synapse maturation is critically dependent upon activation of NMDA-type glutamate receptors (Henson et al., 2012). General role in biology: The development of neuronal networks can be distinguished into two phases: an early ‘establishment’ phase of neuronal connections, where activity-dependent and independent mechanisms could operate, and a later ‘maintenance’ phase, which appears to be controlled by neuronal activity (Yuste and Sur, 1999). These neuronal networks facilitate information flow that is necessary to produce complex behaviors, including learning and memory (Mayford et al., 2012).

Methods that have been previously reviewed and approved by a recognized authority should be included in the Overview section above. All other methods, including those well established in the published literature, should be described here. Consider the following criteria when describing each method: 1. Is the assay fit for purpose? 2. Is the assay directly or indirectly (i.e. a surrogate) related to a key event relevant to the final adverse effect in question? 3. Is the assay repeatable? 4. Is the assay reproducible? In vivo: The recording of brain activity by using electroencephalography (EEG), electrocorticography (ECoG) and local field potentials (LFP) assists towards the collection of signals generated by multiple neuronal cell networks. Advances in computer technology have allowed quantification of the EEG and expansion of quantitative EEG (qEEG) analysis providing a sensitive tool for time-course studies of different compounds acting on neuronal networks' function (Binienda et al., 2011). The number of excitatory or inhibitory synapses can be functionally studied at an electrophysiological level by examining the contribution of glutamatergic and GABAergic synaptic inputs. The number of them can be determined by variably clamping the membrane potential and recording excitatory and inhibitory postsynaptic currents (EPSCs or IPSCs) (Liu, 2004). In vitro: Microelectrode array (MEA) recordings are also used to measure electrical activity in cultured neurons (Keefer et al., 2001, Gramowski et al., 2000; Gopal, 2003; Johnstone et al., 2010). MEAs can be applied in high throughput platforms to facilitate screening of numerous chemical compounds (McConnell et al., 2012). Using selective agonists and antagonists of different classes of receptors their response can be evaluated in a quantitative manner (Novellino et al., 2011; Hogberg et al., 2011). Patch clamping technique can also be used to measure neuronal network activity.In some cases, if required, planar patch clamping technique can also be used to measure neuronal networks activity (e.g., Bosca et al., 2014).

In vitro studies in brain slices applying electrophysiological techniques showed significant variability among species (immature rats, rabbits and kittens) related to synaptic latency, duration, amplitude and efficacy in spike initiation (reviewed in Erecinska et al., 2004).

UBERON:0000955

UBERON brain

High Mixed

High

During brain development

High High High High

Adams MM, Flagg RA, Gore AC., Perinatal changes in hypothalamic N-methyl-D-aspartate receptors and their relationship to gonadotropin-releasing hormone neurons. Endocrinology. 1999 May;140(5):2288-96. Binienda ZK, Beaudoin MA, Thorn BT, Ali SF. (2011) Analysis of electrical brain waves in neurotoxicology: γ-hydroxybutyrate. Curr Neuropharmacol. 9: 236-239. Bosca, A., M. Martina, and C. Py (2014) Planar patch clamp for neuronal networks--considerations and future perspectives. Methods Mol Biol, 2014. 1183: p. 93-113. Erecinska M, Cherian S, Silver IA. (2004) Energy metabolism in mammalian brain during development. Prog Neurobiol. 73: 397-445. Gambrill AC, Barria A. NMDA receptor subunit composition controls synaptogenesis and synapse stabilization. Proc Natl Acad Sci U S A. 2011:108(14):5855-60. Gopal K. (2003) Neurotoxic effects of mercury on auditory cortex networks growing on microelectrode arrays: a preliminary analysis. Neurotoxicol Teratol. 25: 69-76. Gramowski A, Schiffmann D, Gross GW. (2000) Quantification of acute neurotoxic effects of trimethyltin using neuronal networks cultures on microelectrode arrays. Neurotoxicology 21: 331-342. Henson MA, Larsen RS, Lawson SN, Pérez-Otaño I, Nakanishi N, Lipton SA, Philpot BD. (2012) Genetic deletion of NR3A accelerates glutamatergic synapse maturation. PLoS One. 7(8). Hogberg HT, Sobanski T, Novellino A, Whelan M, Weiss DG, Bal-Price AK. (2011) Application of micro-electrode arrays (MEAs) as an emerging technology for developmental neurotoxicity: evaluation of domoic acid-induced effects in primary cultures of rat cortical neurons. Neurotoxicology 32: 158-168. Johnstone AFM, Gross GW, Weiss D, Schroeder O, Shafer TJ. (2010) Use of microelectrode arrays for neurotoxicity testing in the 21st century Neurotoxicology 31: 331-350. Keefer E, Norton S, Boyle N, Talesa V, Gross G. (2001) Acute toxicity screening of novel AChE inhibitors using neuronal networks on microelectrode arrays. Neurotoxicology 22: 3-12. Liu G. (2004) Local structural balance and functional interaction of excitatory and inhibitory synapses in hippocampal dendrites. Nat Neurosci. 7: 373-379. Mayford M, Siegelbaum SA, Kandel ER. (2012) Synapses and memory storage. Cold Spring Harb Perspect Biol. 4. pii: a005751. McConnell ER, McClain MA, Ross J, LeFew WR, Shafer TJ. (2012) Evaluation of multi-well microelectrode arrays for neurotoxicity screening using a chemical training set. Neurotoxicology 33: 1048-1057. Novellino A, Scelfo B, Palosaari T, Price A, Sobanski T, Shafer TJ, Johnstone AF, Gross GW, Gramowski A, Schroeder O, Jügelt K, Chiappalone M, Benfenati F, Martinoia S, Tedesco MT, Defranchi E, D'Angelo P, Whelan M. (2011) Development of micro-electrode array based tests for neurotoxicity: assessment of interlaboratory reproducibility with neuroactive chemicals. Front Neuroeng. 4: 4. Yuste R, Peinado A, Katz LC. (1992) Neuronal domains in developing neocortex. Science 257: 665-669. AOPWiki 2016-11-29T18:41:24

2018-05-28T11:36:00

Impairment, Learning and memory

Individual

(Adapted from <a href="https://aopwiki.org/events/341" rel="noreferrer noopener" target="_blank">KE: 341</a> - in blue)  Learning can be defined as the process by which new information is acquired to establish knowledge by systematic study or by trial and error (Ono, 2009). Two types of learning are considered in neurobehavioral studies: a) associative learning and b) non- associative learning. Associative learning is based on making associations between different events. In associative learning, a subject learns the relationship among two different stimuli or between the stimulus and the subject’s behavior. On the other hand, non-associative learning can be defined as an alteration in the behavioral response that occurs over time in response to a single type of stimulus. Habituation and sensitization are some examples of non-associative learning.  The memory formation requires acquisition, retention and retrieval of information in the brain, which is characterized by the non- conscious recall of information (Ono, 2009). There are three main categories of memory, including sensory memory, short-term or working memory (up to a few hours) and long-term memory (up to several days or even much longer).  Learning and memory depend upon the coordinated action of different brain regions and neurotransmitter systems constituting functionally integrated neural networks (D’Hooge and DeDeyn, 2001). Among the many brain areas engaged in the acquisition of, or retrieval of, a learned event, the hippocampal-based memory systems have received the most study. For example, the hippocampus has been shown to be critical for spatial-temporal memory, visio-spatial memory, verbal and narrative memory, and episodic and autobiographical memory (Burgess et al., 2000; Vorhees and Williams, 2014). However, there is substantial evidence that fundamental learning and memory functions are not mediated by the hippocampus alone but require a network that includes, in addition to the hippocampus, anterior thalamic nuclei, mammillary bodies cortex, cerebellum and basal ganglia (Aggleton and Brown, 1999; Doya, 2000; Mitchell et al., 2002, Toscano and Guilarte, 2005; Gilbert et al., 2006, 2016). Thus, damage to variety of    brain structures can potentially lead to impairment of learning and memory. The main learning areas and pathways are similar in rodents and primates, including man (Eichenbaum, 2000; Stanton and Spear, 1990). While the prefrontal cortex and frontostriatal neural circuits have been identified as the primary sites of higher-order cognition in vertebrates, invertebrates utilize paired mushroom bodies, shown to contain ~300,000 neurons in honey bees (Menzel, 2012; Puig et al., 2014).  For the purposes of this KE (AO), impaired learning and memory is defined as an organism’s inability to establish new associative or non-associative relationships, or sensory, short-term or long-term memories which can be measured using different behavioral tests described below.

In laboratory animals: in rodents, a variety of tests of learning and memory have been used to probe the integrity of hippocampal function. These include tests of spatial learning like the radial arm maze (RAM), the Barnes maze, Hebb-Williams maze, passive avoidance and Spontaneous alternation and most commonly, the Morris water maze (MWM). Test of novelty such as novel object recognition, and fear based context learning are also sensitive to hippocampal disruption. Finally, trace fear conditioning which incorporates a temporal component upon traditional amygdala-based fear learning engages the hippocampus. A brief description of these tasks follows.  RAM, Barnes, MWM, Hebb-Williams maze are examples of spatial tasks, animals are required to learn the location of a food reward (RAM); an escape hole to enter a preferred dark tunnel from a brightly lit open field area (Barnes maze), or a hidden platform submerged below the surface of the water in a large tank of water (MWM) (Vorhees and Williams, 2014). The Hebb- Williams maze measures an animal’s problem solving abilities by providing no spatial cues to find the target (Pritchett & Mulder, 2004).  Novel Object recognition. This is a simpler task that can be used to probe recognition memory. Two objects are presented to animal in an open field on trial 1, and these are explored. On trial 2, one object is replaced with a novel object and time spent interacting with the novel object is taken evidence of memory retention – I have seen one of these objects before, but not this one (Cohen and Stackman, 2015).  Contextual Fear conditioning is a hippocampal based learning task in which animals are placed in a novel environment and allowed to explore for several minutes before delivery of an aversive stimulus, typically a mild foot shock. Upon reintroduction to this same environment in the future (typically 24-48 hours after original training), animals will limit their exploration, the context of this chamber being associated with an aversive event. The degree of suppression of activity after training is taken as evidence of retention, i.e., memory (Curzon et al., 2009).  Trace fear conditioning. Standard fear conditioning paradigms require animals to make an association between a neutral conditioning stimulus (CS, a light or a tone) and an aversive stimulus (US, a footshock). The unconditioned response (CR) that is elicited upon delivery of the footshock US is freezing behavior. With repetition of CS/US delivery, the previously neutral stimulus comes to elicit the freezing response. This type of learning is dependent on the amygdala, a brain region associated with, but distinct from the hippocampus. Introducing a brief delay between presentation of the neutral CS and the aversive US, a trace period, requires the engagement of the amygdala and the hippocampus (Shors et al., 2001).  Operant Responding. Performance on operant responding reflects the cortex’ ability to organize processes (Rabin et al., 2002).  In humans: A variety of standardized learning and memory tests have been developed for human neuropsychological testing, including children (Rohlman et al., 2008). These include episodic autobiographical memory, perceptual motor tests, short and long term memory tests, working memory tasks, word pair recognition memory; object location recognition memory. Some have been incorporated in general tests of intelligence (IQ) such as the Wechsler Adult Intelligence Scale (WAIS) and the Wechsler.  Modifications have been made and norms developed for incorporating of tests of learning and memory in children. Examples of some of these tests include:  Rey Osterieth Complex Figure test (RCFT) which probes a variety of functions including as visuospatial abilities, memory, attention, planning, and working memory (Shin et al., 2006).  Children’s Auditory Verbal Learning Test (CAVLT) is a free recall of presented word lists that yields measures of Immediate Memory Span, Level of Learning, Immediate Recall, Delayed Recall, Recognition Accuracy, and Total Intrusions. (Lezak 1994; Talley, 1986).  Continuous Visual Memory Test (CVMT) measures visual learning and memory. It is a free recall of presented pictures/objects rather than words but that yields similar measures of Immediate Memory Span, Level of Learning, Immediate Recall, Delayed Recall, Recognition Accuracy, and Total Intrusions. (Lezak, 1984; 1994).  Story Recall from Wechsler Memory Scale (WMS) Logical Memory Test Battery, a standardized neurospychological test designed to measure memory functions (Lezak, 1994; Talley, 1986).  Autobiographical memory (AM) is the recollection of specific personal events in a multifaceted higher order cognitive process. It includes episodic memory- remembering of past events specific in time and place, in contrast to semantic autobiographical memory is the recollection of personal facts, traits, and general knowledge. Episodic AM is associated with greater activation of the hippocampus and a later and more gradual developmental trajectory. Absence of episodic memory in early life (infantile amnesia) is thought to reflect immature hippocampal function (Herold et al., 2015; Fivush, 2011).    Staged Autobiographical Memory Task. In this version of the AM test, children participate in a staged event involving a tour of the hospital, perform a series of tasks (counting footprints in the hall, identifying objects in wall display, buy lunch, watched a video). It is designed to contain unique event happenings, place, time, visual/sensory/perceptual details. Four to five months later, interviews are conducted using Children’s Autobiographical Interview and scored according to standardized scheme (Willoughby et al., 2014).  Attentional set-shifting (ATSET) task. Measures the ability to relearn cues over various schedules of reinforcement (Heisler et al., 2015).  In Honey Bees: For over 50 years an assay for evaluating olfactory conditioning of the proboscis extension reflex (PER) has been used as a reliable method for evaluating appetitive learning and memory in honey bees (Guirfa and Sandoz, 2012; LaLone et al., 2017). These experiments pair a conditioned stimulus (e.g., an odor) with an unconditioned stimulus (e.g., sucrose) provided immediately afterward, which elicits the proboscis extension (Menzel, 2012). After conditioning, the odor alone will lead to the conditioned PER. This methodology has aided in the elucidation of five types of olfactory memory phases in honey bee, which include early short-term memory, late short-term memory, mid-term memory, early long-term memory, and late long-term memory (Guirfa and Sandoz, 2012). These phases are dependent on the type of conditioned stimulus, the intensity of the unconditioned stimulus, the number of conditioning trials, and the time between trials. Where formation of short-term memory occurs minutes after conditioning and decays within minutes, memory consolidation or stabilization of a memory trace after initial acquisition leads to  mid-term memory, which lasts 1 d and is characterized by activity of the cAMP-dependent PKA (Guirfa and Sandoz, 2012). Multiple conditioning trials increase the duration of the memory after learning and coincide with increased Ca2+-calmodulin-dependent PKC activity (Guirfa and Sandoz, 2012). Early long-term memory, where a conditioned response can be evoked days to weeks after conditioning requires translation of existing mRNA, whereas late long-term memory requires de novo gene transcription and can last for weeks (Guirfa andSandoz, 2012)."

Basic forms of learning behavior such as habituation have been found in many taxa from worms to humans (Alexander, 1990). More complex cognitive processes such as executive function likely reside only in higher mammalian species such as non-human primates and humans. Recently, larval zebrafish has also been suggested as a model for the study of learning and memory (Roberts et al., 2013).  Life stage applicability: This key event is applicable to various life stages such as during brain development and maturity (Hladik & Tapio, 2016).  Sex applicability: This key event is not sex specific (Cekanaviciute et al., 2018), although sex-dependent cognitive outcomes have been recently ; Parihar et al., 2020).  Evidence for perturbation by a prototypic stressor: Current literature provides ample evidence of impaired learning and memory being induced by ionizing radiation (Cekanaviciute et al., 2018; Hladik & Tapio, 2016).

High Mixed

High

During brain development

High

Adult, reproductively mature

High High High High High High

Aggleton JP, Brown MW. (1999) Episodic memory, amnesia, and the hippocampal-anterior thalamic axis. Behav Brain Sci. 22: 425- 489.  Alexander RD (1990) Epigenetic rules and Darwinian algorithms: The adaptive study of learning and development. Ethology and Sociobiology 11:241-303.  Bellinger DC (2012) A strategy for comparing the contributions of environmental chemicals and other risk factors to neurodevelopment of children. Environ Health Perspect 120:501-507.  Burgess N (2002) The hippocampus, space, and viewpoints in episodic memory. Q J Exp Psychol A 55:1057-1080. Cohen, SJ and Stackman, RW. (2015). Assessing rodent hippocampal involvement in the novel object recognition task. A review. Behav. Brain Res. 285: 105-1176.  Cekanaviciute, E., S. Rosi and S. Costes. (2018), "Central Nervous System Responses to Simulated Galactic Cosmic Rays", International Journal of Molecular Sciences, Vol. 19/11, Multidisciplinary Digital Publishing Institute (MDPI) AG, Basel, https://doi.org/10.3390/ijms19113669.  Cohen, SJ and Stackman, RW. (2015). Assessing rodent hippocampal involvement in the novel object recognition task. A review. Behav. Brain Res. 285: 105-1176.  Curzon P, Rustay NR, Browman KE. Cued and Contextual Fear Conditioning for Rodents. In: Buccafusco JJ, editor. Methods of Behavior Analysis in Neuroscience. 2nd edition. Boca Raton (FL): CRC Press/Taylor & Francis; 2009.  D'Hooge R, De Deyn PP (2001) Applications of the Morris water maze in the study of learning and memory. Brain Res Brain Res Rev 36:60-90.  Doya K. (2000) Complementary roles of basal ganglia and cerebellum in learning and motor control. Curr Opin Neurobiol. 10: 732- 739.    Eichenbaum H (2000) A cortical-hippocampal system for declarative memory. Nat Rev Neurosci 1:41-50. Fivush R. The development of autobiographical memory. Annu Rev Psychol. 2011;62:559-82.  Gilbert ME, Sanchez-Huerta K, Wood C (2016) Mild Thyroid Hormone Insufficiency During Development Compromises Activity- Dependent Neuroplasticity in the Hippocampus of Adult Male Rats. Endocrinology 157:774-787.  Gilbert ME, Rovet J, Chen Z, Koibuchi N. (2012) Developmental thyroid hormone disruption: prevalence, environmental contaminants and neurodevelopmental consequences. Neurotoxicology 33: 842-52.  Gilbert ME, Sui L (2006) Dose-dependent reductions in spatial learning and synaptic function in the dentate gyrus of adult rats following developmental thyroid hormone insufficiency. Brain Res 1069:10-22.  Guirfa, M., Sandoz, J.C., 2012. Invertebrate learning and memory: fifty years of olfactory conditioning of the proboscis extension response in honeybees. Learn. Mem. 19 (2),  54–66.  Herold, C, Lässer, MM, Schmid, LA, Seidl, U, Kong, L, Fellhauer, I, Thomann,PA, Essig, M and Schröder, J. (2015). Neuropsychology, Autobiographical Memory, and Hippocampal Volume in “Younger” and “Older” Patients with Chronic Schizophrenia. Front. Psychiatry, 6: 53.  Hladik, D. and S. Tapio. (2016), "Effects of ionizing radiation on the mammalian brain", Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier B. b., Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003.  Heisler, J. M. et al. (2015), "The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice", Journal of Visualized Experiments, 96, JoVe, Cambridge, https://doi.org/10.3791/51944.   LaLone, C.A., Villeneuve, D.L., Wu-Smart, J., Milsk, R.Y., Sappington, K., Garber, K.V., Housenger, J. and Ankley, G.T., 2017. Weight of evidence evaluation of a network of adverse outcome pathways linking activation of the nicotinic acetylcholine receptor in honey bees to colony death. STOTEN. 584-585, 751-775.  Lezak MD (1984) Neuropsychological assessment in behavioral toxicology--developing techniques and interpretative issues. Scand J Work Environ Health 10 Suppl 1:25-29.  Lezak MD (1994) Domains of behavior from a neuropsychological perspective: the whole story. Nebr Symp Motiv 41:23-55.  Makris SL, Raffaele K, Allen S, Bowers WJ, Hass U, Alleva E, Calamandrei G, Sheets L, Amcoff P, Delrue N, Crofton KM. (2009) A retrospective performance assessment of the developmental neurotoxicity study in support of OECD test guideline 426. Environ Health Perspect. Jan;117(1):17-25.  Menzel, R., 2012. The honeybee as a model for understanding the basis of cognition. Nat. Rev. Neurosci. 13 (11), 758–768.  Mitchell AS, Dalrymple-Alford JC, Christie MA. (2002) Spatial working memory and the brainstem cholinergic innervation to the anterior thalamus. J Neurosci. 22: 1922-1928.  OECD. 2007. OECD guidelines for the testing of chemicals/ section 4: Health effects. Test no. 426: Developmental neurotoxicity study. www.Oecd.Org/dataoecd/20/52/37622194.Pdf [accessed may 21, 2012].  OECD (2008) Nr 43 GUIDANCE DOCUMENT ON MAMMALIAN REPRODUCTIVE TOXICITY TESTING AND ASSESSMENT. ENV/JM/MONO(2008)16  Ono T. (2009) Learning and Memory. Encyclopedia of neuroscience. M D. Binder, N. Hirokawa and U. Windhorst (Eds). Springer- Verlag GmbH Berlin Heidelberg. pp 2129-2137.  Parihar, V. K. et al. (2020), "Sex-Specific Cognitive Deficits Following Space Radiation Exposure", Frontiers in Behavioral Neuroscience, Vol. 14, https://doi.org/10.3389/fnbeh.2020.535885.  Pritchett, K. and G. Mulder. (2004), "Hebb-Williams mazes.", Contemporary topics in laboratory animal science, Vol. 43/5, http://www.ncbi.nlm.nih.gov/pubmed/15461441.  Puig, M.V., Antzoulatos, E.G., Miller, E.K., 2014. Prefrontal dopamine in associative learning and memory. Neuroscience 282, 217– 229.  Rabin, B. M. et al. (2002), "Effects of Exposure to 56Fe Particles or Protons on Fixed-ratio Operant Responding in Rats", Journal of Radiation Research, Vol. 43/S, https://doi.org/10.1269/jrr.43.S225.  Roberts AC, Bill BR, Glanzman DL. (2013) Learning and memory in zebrafish larvae. Front Neural Circuits 7: 126.  Rohlman DS, Lucchini R, Anger WK, Bellinger DC, van Thriel C. (2008) Neurobehavioral testing in human risk assessment. Neurotoxicology. 29: 556-567.  Shin, MS, Park, SY, Park, SR, Oeol, SH and Kwon, JS. (2006). Clinical and empirical applications of the Rey-Osterieth complex figure test. Nature Protocols, 1: 892-899.    Shors TJ, Miesegaes G, Beylin A, Zhao M, Rydel T, Gould E (2001) Neurogenesis in the adult is involved in the formation of trace memories. Nature 410:372-376.  Stanton ME, Spear LP (1990) Workshop on the qualitative and quantitative comparability of human and animal developmental neurotoxicity, Work Group I report: comparability of measures of developmental neurotoxicity in humans and laboratory animals. Neurotoxicol Teratol 12:261-267.  Talley, JL. (1986). Memory in learning disabled children: Digit span and eh Rey Auditory verbal learning test. Archives of Clinical Neuropsychology, Elseiver.  Toscano CD, Guilarte TR. (2005) Lead neurotoxicity: From exposure to molecular effects. Brain Res Rev. 49: 529-554.  U.S.EPA. 1998. Health effects guidelines OPPTS 870.6300 developmental neurotoxicity study. EPA Document 712-C-98-239.Office of Prevention Pesticides and Toxic Substances.  Vorhees CV, Williams MT (2014) Assessing spatial learning and memory in rodents. ILAR J 55:310-332.  Willoughby KA, McAndrews MP, Rovet JF. Accuracy of episodic autobiographical memory in children with early thyroid hormone deficiency using a staged event. Dev Cogn Neurosci. 2014 Jul;9:1-11.     AOPWiki 2016-11-29T18:41:24

2024-07-26T09:54:11

Retinoic acid receptor antagonism during neurodevelopment leading to impaired learning and memory

RAR antagonism during neurodevelopment leading to impaired learning and memory

Diana Lupu

Open for adoption

2.6

A prime example of impairments in learning and memory as the adverse outcome for regulatory action is developmental lead exposure and IQ function in children (Bellinger, 2012). Most methods are well established in the published literature and many have been engaged to evaluate the effects of developmental thyroid disruption. The US EPA and OECD Developmental Neurotoxicity (DNT) Guidelines (OCSPP 870.6300 or OECD TG 426) as well as OECD TG 443 (OECD, 2018) both require testing of learning and memory (USEPA, 1998; OECD, 2007) advising to use the following tests passive avoidance, delayed-matching-to-position for the adult rat and for the infant rat, olfactory conditioning, Morris water maze, Biel or Cincinnati maze, radial arm maze, T-maze, and acquisition and retention of schedule-controlled behavior. These DNT Guidelines have been deemed valid to identify developmental neurotoxicity and adverse neurodevelopmental outcomes (Makris et al., 2009).  Also, in the frame of the OECD GD 43 (2008) on reproductive toxicity, learning and memory testing may have potential to be applied in the context of developmental neurotoxicity studies. However, many of the learning and memory tasks used in guideline studies may not readily detect subtle impairments in cognitive function associated with modest degrees of developmental thyroid disruption (Gilbert et al., 2012).

AOPWiki 2024-05-27T03:25:46

2024-06-06T12:32:03