Psychological experiments have shown that the capacity of the brain for discriminating visual stimuli as novel or familiar is almost limitless. Neurobiological studies have established that the perirhinal cortex is critically involved in both familiarity discrimination and feature extraction. However, opinion is divided as to whether these two processes are performed by the same neurons. Previously proposed models have been unable to simultaneously extract features and discriminate familiarity for large numbers of stimuli. We show that a well-known model of visual feature extraction, Infomax, can simultaneously perform familiarity discrimination and feature extraction efficiently. This model has a significantly larger capacity than previously proposed models combining these two processes, particularly when correlation exists between inputs, as is the case in the perirhinal cortex. Furthermore, we show that once the model fully extracts features, its ability to perform familiarity discrimination increases markedly.
Table of contentsA1 Functional advantages of cell-type heterogeneity in neural circuitsTatyana O. SharpeeA2 Mesoscopic modeling of propagating waves in visual cortexAlain DestexheA3 Dynamics and biomarkers of mental disordersMitsuo KawatoF1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneuronsVladislav Sekulić, Frances K. SkinnerF2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brainsDaniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán SomogyváriF3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir JosićO1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generatorsIrene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo VaronaO2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrainEunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun ChoiO3 Modeling auditory stream segregation, build-up and bistabilityJames Rankin, Pamela Osborn Popp, John RinzelO4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fieldsAlejandro Tabas, André Rupp, Emili Balaguer-BallesterO5 A simple model of retinal response to multi-electrode stimulationMatias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish MeffinO6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination taskVeronika Koren, Timm Lochmann, Valentin Dragoi, Klaus ObermayerO7 Input-location dependent gain modulation in cerebellar nucleus neuronsMaria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker SteuberO8 Analytic solution of cable energy function for cortical axons and dendritesHuiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo YuO9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal networkJimin Kim, Will Leahy, Eli ShlizermanO10 Is the model any good? Objective criteria for computational neuroscience model selectionJustas Birgiolas, Richard C. Gerkin, Sharon M. CrookO11 Cooperation and competition of gamma oscillation mechanismsAtthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan GielenO12 A discrete structure of the brain wavesYuri Dabaghian, Justin DeVito, Luca PerottiO13 Direction-specific silencing of the Drosophila gaze stabilization systemAnmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby MaimonO14 What does the fruit fly think about values? A model of olfactory associative learningChang Zhao, Yves Widmer, Simon Sprecher,Walter SennO15 Effects of ionic diffusion on power spectra of local field potentials (LFP)Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen...
The aging brain undergoes remodeling processes because of biological and environmental factors. To counteract brain aging, neuronal plasticity should be preserved. The aim of this study was to test if the capacity of generating short-time synaptic plasticity in older adults may be related to either physical activity, nutritional status, cognition, or neurophysiological activity. Thirty-six participants (mean age 73.3 ± 5.9 years) received transcranial magnetic stimulation in combination with peripheral nerve stimulation to experimentally induce short-time synaptic plasticity by paired associative stimulation (PAS). Adaptations in neuronal excitability were assessed by motor-evoked potential (MEP) in the right m. tibialis anterior before and after PAS. The Physical Activity Questionnaire 50+ and the StepWatchTM captured physical activity levels. Nutritional status was assessed by the Mini Nutritional Assessment. Cognition was assessed by reaction time for a divided attention test and with the Montreal Cognitive Assessment. Neurophysiological activity was assessed by electroencephalography during the divided attention test. MEPs of the highest stimulation intensity resulted significantly different comparing before, 5 min, or 30 min after PAS (p < 0.05). Data-driven automatic hierarchical classification of the individual recruitment curve slopes over the three-time points indicated four different response types, however, response groups did not significantly differ based on physical activity, nutritional status, cognition, or neurophysiological activity. In a second-level analysis, participants having an increased slope showed a significant higher energy expenditure (z = -2.165, p = 0.030, r = 0.36) and revealed a significant higher power activity in the alpha frequency band (z = -2.008, p = 0.046, r = 0.37) at the prefrontal-located EEG electrodes, compared to the participants having a decreased slope. This study hints toward older adults differing in their neuronal excitability which is strongly associated to their short-time synaptic plasticity levels. Furthermore, a physically active lifestyle and higher EEG power in the alpha frequency band seem to be connected to the capacity of generating long-term potentiation-like synaptic plasticity in older adults. Future studies should consider more sensitive assessments and bigger sample sizes to get a broad scope of the older adults’ population.
Spike timing dependent plasticity (STDP) likely plays an important role in forming and changing connectivity patterns between neurons in our brain. In a unidirectional synaptic connection between two neurons, it uses the causal relation between spiking activity of a presynaptic input neuron and a postsynaptic output neuron to change the strength of this connection. While the nature of STDP benefits unsupervised learning of correlated inputs, any incorporation of value into the learning process needs some form of reinforcement. Chemical neuromodulators such as Dopamine or Acetylcholine are thought to signal changes between external reward and internal expectation to many brain regions, including the basal ganglia. This effect is often modelled through a direct inclusion of the level of Dopamine as a third factor into the STDP rule. While this gives the benefit of direct control over synaptic modification, it does not account for observed instantaneous effects in neuronal activity on application of Dopamine agonists. Specifically, an instant facilitation of neuronal excitability in the striatum can not be explained by the only indirect effect that dopamine-modulated STDP has on a neuron's firing pattern. We therefore propose a model for synaptic transmission where the level of neuromodulator does not directly influence synaptic plasticity, but instead alters the relative firing causality between preand postsynaptic neurons. Through the direct effect on postsynaptic activity, our rule allows indirect modulation of the learning outcome even with unmodulated, two-factor STDP. However, it also does not prohibit joint operation together with three-factor STDP rules.
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