Abstract
This chapter describes the role of single-cell recordings in understanding the mechanisms underlying human cognition. Cognition is a function of the brain, a complex computational network, whose most elementary nodes are made up out of individual neurons. These neurons encode information and influence each other through a dynamically changing pattern of action potentials. For this reason, the activity of neurons in the awake, behaving brain constitutes the most fundamental form of neural data for cognitive neuroscience. This chapter discusses a number of technical issues and challenges of single-cell neurophysiology using a recent project of the authors as an example. We discuss issues such as the choice of an appropriate animal model, the role of psychophysics, technical challenges surrounding the simultaneous recording of multiple neurons, and various methods for perturbation experiments. The chapter closes with a consideration of the challenge that the brain’s complexity poses for fully understanding any realistic nervous circuit, and of the importance of conceptual insights and mathematical models in the interpretation of single-cell recordings.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Teller DY (1984) Linking propositions. Vision Res 24(10):1233–1246
Schall JD (2004) On building a bridge between brain and behavior. Ann Rev Psychol 55:23–50
Parker AJ, Newsome WT (1998) Sense and the single neuron: probing the physiology of perception. Ann Rev Neurosci 21:227–277
Adrian ED (1928) The basis of sensation: the action of the sense organs. W. W. Norton, New York
Hartline HK, Milne LJ, Wagman IH (1947) Fluctuation of response of single visual sense cells. Fed Proc 6(1 Pt 2):124
Barlow HB (1995) The neuron doctrine in perception. In: Gazzaniga MS (ed) The cognitive neurosciences. MIT Press, Cambridge, pp 415–435
Mountcastle VB, Talbot WH, Darian-Smith I, Kornhuber HH (1967) Neural basis of the sense of flutter-vibration. Science 155(762):597–600
Rieke F, Warland DK, de Ruyter van Steveninck R, Bialek W (1997) Spikes: exploring the neural code. MIT Press, Cambridge
Koch C (1999) Biophysics of computation: information processing in single neurons. In: Computational Neuroscience Series, Stryker M (ed) Oxford University Press, Oxford
Silver RA (2010) Neuronal arithmetic. Nat Rev Neurosci 11(7):474–489
Softky WR, Koch C (1993) The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J Neurosci 13(1):334–350
Shadlen MN, Newsome WT (1998) The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J Neurosci 18(10):3870–3896
Singer W, Gray CM (1995) Visual feature integration and the temporal correlation hypothesis. Ann Rev Neurosci 18:555–586
London M, Roth A, Beeren L, Hausser M, Latham PE (2010) Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466(7302):123–127
Werner G, Mountcastle VB (1965) Neural activity in mechanoreceptive cutaneous afferents: stimulus-response relations, weber functions, and information transmission. J Neurophysiol 28:359–397.
de Lafuente V Romo R (2005) Neuronal correlates of subjective sensory experience. Nature Neuroscience. [Research Support, Non-U.S. Gov't]. 8(12):1698–1703
Newsome WT, Britten KH, Salzman CD, Movshon JA (1990) Neuronal mechanisms of motion perception. Cold Spring Harb Symp Quant Biol 55:697–705
Shadlen MN, Newsome WT (2001) Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol 86(4):1916–1936
Vallbo AB, Johansson RS (1984) Properties of cutaneous mechanoreceptors in the human hand related to touch sensation. Hum Neurobiol 3(1):3–14
Houweling AR, Brecht M (2008) Behavioural report of single neuron stimulation in somatosensory cortex. Nature 451(7174):65–68
Li CY, Poo MM, Dan Y.(2009) Burst spiking of a single cortical neuron modifies global brain state. Science 324(5927):643–646
Crist RE, Lebedev MA (2007) Multielectrode recording in behaving monkeys. In: Nicolelis MAL (ed) Methods for neural ensemble recordings. CRC, Boca Raton
Evarts EV (1966) Pyramidal tract activity associated with a conditioned hand movement in the monkey. J Neurophysiol 29(6):1011–1027
Evarts EV (1968) Relation of pyramidal tract activity to force exerted during voluntary movement. J Neurophysiol 31(1):14–27
Mountcastle VB, Talbot WH, Sakata H, Hyvarinen J (1969) Cortical neuronal mechanisms in flutter-vibration studied in unanesthetized monkeys. Neuronal periodicity and frequency discrimination. J Neurophysiol 32(3):452–484
Wurtz RH (1968) Visual cortex neurons: response to stimuli during rapid eye movements. Science 162(858):1148–1150
Kepecs A, Uchida N, Zariwala HA, Mainen ZF (2008) Neural correlates, computation and behavioural impact of decision confidence. Nature 455(7210):227–231
Ogawa M, van der Meer MA, Esber GR, Cerri DH, Stalnaker TA, Schoenbaum G (2013) Risk-responsive orbitofrontal neurons track acquired salience. Neuron 77(2):251–258
Ohki K, Chung S, Kara P, Hubener M, Bonhoeffer T, Reid RC (2006) Highly ordered arrangement of single neurons in orientation pinwheels. Nature 442(7105):925–958
Denk W, Briggman KL, Helmstaedter M.(2012) Structural neurobiology: missing link to a mechanistic understanding of neural computation. Nat Rev Neurosci.13(5):351–358
Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K (2005) Millisecond-timescale, genetically targeted optical control of neural activity. Nat Neurosci 8(9):1263–1268
Wise SP (2008) Forward frontal fields: phylogeny and fundamental function. Trends Neurosci 31(12):599–608
Tanji J, Hoshi E (2008) Role of the lateral prefrontal cortex in executive behavioral control. Physiol Rev 88(1):37–57
Fuster JM (2008) The prefrontal cortex, 4th edn. Academic Press, Amsterdam
Uylings HB, Groenewegen HJ, Kolb B (2003) Do rats have a prefrontal cortex? Behav Brain Res 146(1–2):3–17
Sescousse G, Redoute J, Dreher JC (2010) The architecture of reward value coding in the human orbitofrontal cortex. J Neurosci 30(39):13095–13104
O'Neill M, Schultz W (2010) Coding of reward risk by orbitofrontal neurons is mostly distinct from coding of reward value. Neuron 68(4):789–800
Tobler PN, O'Doherty JP, Dolan RJ, Schultz W (2007) Reward value coding distinct from risk attitude-related uncertainty coding in human reward systems. J Neurophysiol 97(2):1621–1632
Moore EF (1956) Gedanken-experiments on sequential machines. In: Shannon CE, McCarthy J (eds) Automata studies. Princeton University Press, Princeton pp. 129–153
Ridley RM, Haystead TA, Baker HF (1981 Mar) An analysis of visual object reversal learning in the marmoset after amphetamine and haloperidol. Pharmacol Biochem Behav 14(3):345–351
Kruzich PJ, Grandy DK (2004) Dopamine D2 receptors mediate two-odor discrimination and reversal learning in C57BL/6 mice. BMC Neurosci 5:12
Mehta MA, Swainson R, Ogilvie AD, Sahakian BJ, Robbins TW (2001) Improved short-term spatial memory but impaired following the dopamine D-2 agonist bromocriptine reversal learning in human volunteers. Psychopharmacology 159(1):10–20.
Atasoy D, Betley JN, Su HH, Sternson SM (2012) Deconstruction of a neural circuit for hunger. Nature 488(7410):172–177
Plassmann H, O'Doherty J, Shiv B, Rangel A (2008) Marketing actions can modulate neural representations of experienced pleasantness. Proc Natl Acad Sci U S A 105(3):1050–1054
Cavanaugh J, Monosov IE, McAlonan K, Berman R, Smith MK, Cao V et al (2012) Optogenetic inactivation modifies monkey visuomotor behavior. Neuron 76(5):901–907
Nauhaus I, Nielsen KJ, Disney AA, Callaway EM (2012) Orthogonal micro-organization of orientation and spatial frequency in primate primary visual cortex. Nat Neurosci 15(12):1683–1690
Han X, Qian X, Bernstein JG, Zhou HH, Franzesi GT, Stern P et al (2009) Millisecondtimescale optical control of neural dynamics in the nonhuman primate brain. Neuron 62(2):191–198
Ozden I, Wang J, Lu Y, May T, Lee J, Goo W et al (2013) A coaxial optrode as multifunction write-read probe for optogenetic studies in non-human primates. J Neurosci Methods 219:142–154
Diester I, Kaufman MT, Mogri M, Pashaie R, Goo W, Yizhar O et al (2011) An optogenetic toolbox designed for primates. Nat Neurosci 14(3):387–397
Passingham R (2008) What is special about the human brain? Oxford University Press, Oxford
Suthana N, Fried I (2012 Aug) Percepts to recollections: insights from single neuron recordings in the human brain. Trends Cogn Sci 16(8):427–436
Tankus A, Fried I, Shoham S (2012) Structured neuronal encoding and decoding of human speech features. Nat Commun 3:1015
Quiroga RQ, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435(7045):1102–1107
Cerf M, Thiruvengadam N, Mormann F, Kraskov A, Quiroga RQ, Koch C et al (2010) On-line, voluntary control of human temporal lobe neurons. Nature 467(7319):1104–1108
Burbaud P, Clair AH, Langbour N, Fernandez-Vidal S, Goillandeau M, Michelet T et al (2013) Neuronal activity correlated with checking behaviour in the subthalamic nucleus of patients with obsessive-compulsive disorder. Brain 136(Pt 1):304–317
Gold JI, Shadlen MN (2007) The neural basis of decision making. Ann rev neurosci 30:535–574
Rangel A, Camerer C, Montague PR (2008) A framework for studying the neurobiology of value-based decision making. Nat Rev Neurosci 9(7):545–556
Balleine BW, Dickinson A (1998) Goal-directed instrumental action: contingency and incentive learning and their cortical substrates. Neuropharmacology 37(4–5):407–419
Yin HH, Knowlton BJ (2006) The role of the basal ganglia in habit formation. Nat rev Neurosci 7(6):464–476
Daw ND, Niv Y, Dayan P (2005) Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nat Neurosci 8(12):1704–1711
Vickery TJ, Chun MM, Lee D (2011) Ubiquity and specificity of reinforcement signals throughout the human brain. Neuron 72(1):166–177
Padoa-Schioppa C (2011) Neurobiology of economic choice: a good-based model. Annu Rev Neurosci 34:333–359
Kable JW, Glimcher PW (2009) The neurobiology of decision: consensus and controversy. Neuron 63(6):733–745
Plassmann H, O'Doherty J, Rangel A (2007) Orbitofrontal cortex encodes willingness to pay in everyday economic transactions. J Neurosci 27(37):9984–9988
Plassmann H, O'Doherty JP, Rangel A (2010) Appetitive and aversive goal values are encoded in the medial orbitofrontal cortex at the time of decision making. J Neurosci 30(32):10799–10808
Bermudez MA, Schultz W (2010) Reward magnitude coding in primate amygdala neurons. J Neurophysiol 104(6):3424–3432
Grabenhorst F, Hernadi I, Schultz W (2012) Prediction of economic choice by primate amygdala neurons. Proc Natl Acad Sci U S A 109(46):18950–18955
Lau B, Glimcher PW (2007) Action and outcome encoding in the primate caudate nucleus. J Neurosci 27(52):14502–14514
Samejima K, Ueda Y, Doya K, Kimura M (2005) Representation of action-specific reward values in the striatum. Science 310(5752):1337–1340
Kim S, Hwang J, Lee D (2008) Prefrontal coding of temporally discounted values during intertemporal choice. Neuron 59(1):161–172
Hernandez A, Nacher V, Luna R, Zainos A, Lemus L, Alvarez M et al (2010) Decoding a perceptual decision process across cortex. Neuron 66(2):300–314
Seo H, Barraclough DJ, Lee D (2007) Dynamic signals related to choices and outcomes in the dorsolateral prefrontal cortex. Cereb Cortex 17(suppl 1):i110–i117
So NY, Stuphorn V (2010) Supplementary eye field encodes option and action value for saccades with variable reward. J Neurophysiol 104(5):2634–2653
Cisek P (2012) Making decisions through a distributed consensus. Curr Opin Neurobiol 22(6):927–936
Cisek P, Kalaska JF (2010) Neural mechanisms for interacting with a world full of action choices. Ann Rev Neurosci 33:269–298
Platt ML, Glimcher PW (1999) Neural correlates of decision variables in parietal cortex. Nature 400(6741):233–238
Sugrue LP, Corrado GS, Newsome WT (2004) Matching behavior and the representation of value in the parietal cortex. Science 304(5678):1782–1787
Shadlen MN, Kiani R, Hanks TD, Churchland AK (2008) Neurobiology of decision making, an intentional framework. In: Engel C, Singer W (eds) Better than conscious? MIT Press, Cambridge, pp. 71–101
Kingdom FAA, Prins N (2010) Psychophysics: a practical introduction. Academic Press, Amsterdam
Maloney LT, Yang JN (2003) Maximum likelihood difference scaling. J Vis 3(8):573–585
Fechner GT (1876) Vorschule der Aesthetik. Breitkopf & Haerterl, Leibzig
Gescheider GA (1997) Psychophysics: the fundamentals. 3rd edn. Lawrence Erlbaum Assoc., Mahwah
Thurstone LL (1927) A law of comparative judgment. Psychol Rev 34:273–286
McFadden D (1974) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontier in econometrics. Academic Press, NewYork, pp. 105–142
Glimcher P (2011) Foundations of neuroeconomic analysis. Oxford University Press, Oxford
Stevens SS (1951) Handbook of experimental psychology. Wiley, NewYork
Einevoll GT, Franke F, Hagen E, Pouzat C, Harris KD (2012) Towards reliable spike-train recordings from thousands of neurons with multielectrodes. Curr Opin Neurobiol 22(1):11–17
Hernandez A, Nacher V, Luna R, Alvarez M, Zainos A, Cordero S et al (2008) Procedure for recording the simultaneous activity of single neurons distributed across cortical areas during sensory discrimination. Proc Natl Acad Sci U S A 105(43):16785–16790
Kipke DR, Shain W, Buzsaki G, Fetz E, Henderson JM, Hetke JF et al (2008) Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities. J Neurosci 28(46):11830–11838
Du J, Riedel-Kruse IH, Nawroth JC, Roukes ML, Laurent G, Masmanidis SC (2009) High-resolution three-dimensional extracellular recording of neuronal activity with microfabricated electrode arrays. J Neurophysiol 101(3):1671–1678
Kelly RC, Smith MA, Samonds JM, Kohn A, Bonds AB, Movshon JA et al (2007) Comparison of recordings from microelectrode arrays and single electrodes in the visual cortex. J Neurosci 27(2):261–264
Nicolelis MA, Dimitrov D, Carmena JM, Crist R, Lehew G, Kralik JD et al (2003) Chronic, multisite, multielectrode recordings in macaque monkeys. Proc Natl Acad Sci U S A 100(19):11041–11046
McNaughton BL, O'Keefe J, Barnes CA (1983) The stereotrode: a new technique for simultaneous isolation of several single units in the central nervous system from multiple unit records. J Neurosci Methods 8(4):391–397
Buzsaki G (2004) Large-scale recording of neuronal ensembles. Nat Neurosci 7(5):446–451
Miller EK, Wilson MA (2008) All my circuits: using multiple electrodes to understand functioning neural networks. Neuron 60(3):483–488
Fujisawa S, Amarasingham A, Harrison MT, Buzsaki G (2008) Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex. Nat neurosci 11(7):823–833
Seymour JP, Kipke DR (2007) Neural probe design for reduced tissue encapsulation in CNS. Biomaterials 28(25):3594–3607
Salazar RF, Dotson NM, Bressler SL, Gray CM (2012) Content-specific fronto-parietal synchronization during visual working memory. Science 338(6110):1097–1100
Hoffman KL, McNaughton BL (2002) Coordinated reactivation of distributed memory traces in primate neocortex. Science 297(5589):2070–2073
Wilson MA, McNaughton BL (1994) Reactivation of hippocampal ensemble memories during sleep. Science 265(5172):676–679
Cisek P (2012) Making decisions through a distributed consensus. Curr Opin Neurobiol 22(6):927–936
Huerta MF, Kaas JH (1990) Supplementary eye field as defined by intracortical microstimulation: connections in macaques. J Comp Neurol 293:299–330
Ghashghaei HT, Hilgetag CC, Barbas H (2007 Feb 1) Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala. Neuroimage 34(3):905–923
Lau B, Glimcher PW (2008) Value representations in the primate striatum during matching behavior. Neuron 58(3):451–463
Shook BL, Schlag-Rey M, Schlag J (1991) Primate supplementary eye field. II. Comparative aspects of connections with the thalamus, corpus striatum, and related forebrain nuclei. J Comp Neurol 307(4):562–583
Coe B, Tomihara K, Matsuzawa M, Hikosaka O (2002) Visual and anticipatory bias in three cortical eye fields of the monkey during an adaptive decision-making task. J Neurosci 22(12):5081–5090
So NY, Stuphorn V (2010) Supplementary eye field encodes option and action value for saccades with variable reward. J Neurophysiol 104(5):2634–2653
So NY, Stuphorn V (2012) Supplementary eye field encodes reward prediction error. J Neurosci 32(9):2950–2963
Barlow HB, Levick WR, Yoon M (1971) Responses to single quanta of light in retinal ganglion cells of the cat. Vision Res Suppl 3:87–101
Thompson KG, Hanes DP, Bichot NP, Schall JD (1996) Perceptual and motor processing stages identified in the activity of macaque frontal eye field neurons during visual search. J Neurophysiol 76(6):4040–4055
Churchland MM, Yu BM, Sahani M, Shenoy KV (2007) Techniques for extracting single-trial activity patterns from large-scale neural recordings. Curr Opin Neurobiol 17(5):609–618
Duda RO, Hart PE, Stork DG (2000) Pattern classification, 2nd edn. Wiley, NewYork
Broome BM, Jayaraman V, Laurent G (2006) Encoding and decoding of overlapping odor sequences. Neuron 51(4):467–482
Briggman KL, Abarbanel HD, Kristan WB, Jr (2005) Optical imaging of neuronal populations during decision-making. Science 307(5711):896–901
Harvey CD, Coen P, Tank DW (2012) Choice-specific sequences in parietal cortex during a virtual-navigation decision task. Nature 484(7392):62–68
Yu BM, Cunningham JP, Santhanam G, Ryu SI, Shenoy KV, Sahani M (2009) Gaussianprocess factor analysis for low-dimensional single-trial analysis of neural population activity. J Neurophysiol 102(1):614–635
Lomber SG, Payne BR, Horel JA (1999) The cryoloop: an adaptable reversible cooling deactivation method for behavioral or electrophysiological assessment of neural function. J Neurosci Methods 86(2):179–194
Noonan MP, Walton ME, Behrens TE, Sallet J, Buckley MJ, Rushworth MF (2010) Separate value comparison and learning mechanisms in macaque medial and lateral orbitofrontal cortex. P Natl Acad Sci USA 107(47):20547–20552
Alivisatos AP, Chun M, Church GM, Greenspan RJ, Roukes ML, Yuste R (2012)The brain activity map project and the challenge of functional connectomics. Neuron 74(6):970–974.
Koch C (2012) Systems biology. Modular biological complexity. Science 337(6094):531–532
Mountcastle VB (1997) The columnar organization of the neocortex. Brain 120(Pt 4):701–722
Kim TI, McCall JG, Jung YH, Huang X, Siuda ER, Li Y et al (2013) Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science 340(6129):211–216
Abbott A (2013) Neuroscience: solving the brain. Nature 499(7458):272–274
Kim TI et al (2013) Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science 340:211–216
Alivisatos AP et al (2013) Nanotools for neuroscience and brain activity mapping. ACS Nano 7:1850–1866
Acknowledgements
We are grateful to K. Nielsen, D. Sasikumar and E. Emeric for comments on the manuscript. This work was supported by the National Eye Institute through grant R01-EY019039 to VS.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Stuphorn, V., Chen, X. (2015). An Introduction to Neuroscientific Methods: Single-cell Recordings. In: Forstmann, B., Wagenmakers, EJ. (eds) An Introduction to Model-Based Cognitive Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2236-9_6
Download citation
DOI: https://doi.org/10.1007/978-1-4939-2236-9_6
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-2235-2
Online ISBN: 978-1-4939-2236-9
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)