Book contents
- Frontmatter
- Contents
- List of contributors
- Part I Introduction
- Part II Organization of neuronal activity in neuronal populations
- 2 Cellular mechanisms underlying network synchrony in the medial temporal lobe
- 3 Cell assemblies and serial computation in neural circuits
- 4 Neural population recording in behaving animals: constituents of a neural code for behavioral decisions
- 5 Measuring distributed properties of neural representations beyond the decoding of local variables: implications for cognition
- 6 Single-neuron and ensemble contributions to decoding simultaneously recorded spike trains
- Part III Neuronal population information coding and plasticity in specific brain areas
- Part IV Functional integration of different brain areas in information processing and plasticity
- Part V Disturbances of population activity as the basis of schizophrenia
- Part VI Summary, conclusion, and future targets
- Index
- References
3 - Cell assemblies and serial computation in neural circuits
Published online by Cambridge University Press: 14 August 2009
Book contents
- Frontmatter
- Contents
- List of contributors
- Part I Introduction
- Part II Organization of neuronal activity in neuronal populations
- 2 Cellular mechanisms underlying network synchrony in the medial temporal lobe
- 3 Cell assemblies and serial computation in neural circuits
- 4 Neural population recording in behaving animals: constituents of a neural code for behavioral decisions
- 5 Measuring distributed properties of neural representations beyond the decoding of local variables: implications for cognition
- 6 Single-neuron and ensemble contributions to decoding simultaneously recorded spike trains
- Part III Neuronal population information coding and plasticity in specific brain areas
- Part IV Functional integration of different brain areas in information processing and plasticity
- Part V Disturbances of population activity as the basis of schizophrenia
- Part VI Summary, conclusion, and future targets
- Index
- References
Summary
Introduction
Analogies between the brain and the digital computer have been out of fashion for a long time. The differences between brains and computers are numerous. Computers run pre-specified programs written by people. Computers store programs and data in specialized RAM circuits, and have one CPU (or at most a handful) which follows a coded list of instructions to the letter. A computer has a central clock, which allows all of its components to march through a program in lockstep. The brain, on the other hand, has billions of neurons operating in parallel, no central clock, no externally supplied list of instructions, and no separation of RAM and CPU. Although the inventors of the modern computer held the brain as a model, the analogy is rarely taken seriously today.
A more popular analogy for the brain in recent years has been artificial neural networks (ANNs). ANNs, although typically simulated on a digital computer, have an apparently more “brain-like” design. They consist of elements that function (at least a bit) like neurons, connected by “synapses” whose strength can be modified by the network's history. ANNs do not need an external program, but “learn” from a set of training examples. The most successful of these, the multilayer perceptron or “backprop” net, is good enough at generalizing from training examples to be used in real-world information processing tasks, by people who have no interest in how the brain works.
Information
- Type
- Chapter
- Information
- Information Processing by Neuronal Populations , pp. 49 - 73Publisher: Cambridge University PressPrint publication year: 2008
References
and (2001). Detecting precise firing sequences in experimental data. J Neurosci Methods 107:141–154.CrossRefGoogle ScholarPubMed
, , , and (1993). Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. J Neurophysiol 70:1629–1638.CrossRefGoogle ScholarPubMed
and (1926). The impulses produced by sensory nerve endings. II. The response of a single end organ. J Physiol (Lond) 61:151–171.CrossRefGoogle ScholarPubMed
(1994). The Hebbian paradigm reintegrated: local reverberations as internal representations. Behav Brain Sci 18:617–626.CrossRefGoogle Scholar
, , , et al. (1997). Responses of neurons in primary and inferior temporal visual cortices to natural scenes. Proc R Soc Lond B 264:1775–1783.CrossRefGoogle ScholarPubMed
and (1996). Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey. Neural Comput 8:1185–1202.CrossRefGoogle ScholarPubMed
, , and (2001). Correlated firing in macaque visual area MT: time scales and relationship to behavior. J Neurosci 21:1676–1697.CrossRefGoogle Scholar
and (2000). Precise spatiotemporal repeating patterns in monkey primary and supplementary motor areas occur at chance levels. J Neurophysiol 84:1770–1780.CrossRefGoogle ScholarPubMed
(1972). Single units and sensation: a neuron doctrine for perceptual psychology?Perception 1:371–394.CrossRefGoogle ScholarPubMed
, , , et al. (2004). Characterization of neocortical principal cells and interneurons by network interactions and extracellular features. J Neurophysiol 92:600–608.CrossRefGoogle ScholarPubMed
, , and (1997). The structure and precision of retinal spike trains. Proc Natl Acad Sci USA 94:5411–5416.CrossRefGoogle ScholarPubMed
and (1998). Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18:10 464–10 472.CrossRefGoogle ScholarPubMed
, , , and (1993). Responses of neurons in macaque MT to stochastic motion signals. Vis Neurosci 10:1157–1169.CrossRefGoogle ScholarPubMed
, , and (1998). Efficient discrimination of temporal patterns by motion-sensitive neurons in primate visual cortex. Neuron 20:959–969.CrossRefGoogle ScholarPubMed
, , and (2002). Gain modulation from background synaptic input. Neuron 35:773–782.CrossRefGoogle ScholarPubMed
, , and (2001). Coding specificity in cortical microcircuits: a multiple-electrode analysis of primate prefrontal cortex. J Neurosci 21:3646–3655.CrossRefGoogle ScholarPubMed
, , and (2003). Attractor dynamics of network UP states in the neocortex. Nature 423:283–288.CrossRefGoogle ScholarPubMed
, , , and (1998). Reliability and state dependence of pyramidal cell-interneuron synapses in the hippocampus: an ensemble approach in the behaving rat. Neuron 21:179–189.CrossRefGoogle ScholarPubMed
, , , and (2003). Mechanisms of gamma oscillations in the hippocampus of the behaving rat. Neuron 37:311–322.CrossRefGoogle ScholarPubMed
and (2004). Shared and private variability in the auditory cortex. J Neurophysiol 92:1840–1855.CrossRefGoogle ScholarPubMed
, , and (2003). Binary spiking in auditory cortex. J Neurosci 23:7940–7949.CrossRefGoogle ScholarPubMed
and (1996). Primary cortical representation of sounds by the coordination of action-potential timing. Nature 381:610–613.CrossRefGoogle ScholarPubMed
and (2000). Neural representation and the cortical code. Annu Rev Neurosci 23:613–647.CrossRefGoogle ScholarPubMed
and (2003). Taste response variability and temporal coding in the nucleus of the solitary tract of the rat. J Neurophysiol 90:1418–1431.CrossRefGoogle ScholarPubMed
, , and (2001). Dynamic predictions: oscillations and synchrony in top–down processing. Nat Rev Neurosci 2:704–716.CrossRefGoogle ScholarPubMed
, , , and (2004). Discovering spike patterns in neuronal responses. J Neurosci 24:2989–3001.CrossRefGoogle ScholarPubMed
and (1998). Place cell discharge is extremely variable during individual passes of the rat through the firing field. Proc Natl Acad Sci USA 95:3182–3187.CrossRefGoogle ScholarPubMed
, , , and (2001). Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291:1560–1563.CrossRefGoogle ScholarPubMed
, , and (2000). Coding of sound-source location by ensembles of cortical neurons. J Neurosci 20:1216–1228.CrossRefGoogle ScholarPubMed
, , and (1996). From stimulus encoding to feature extraction in weakly electric fish. Nature 384:564–567.CrossRefGoogle ScholarPubMed
(1976). The recall of events through the learning of associations between their parts. Proc R Soc Lond B 194:375–402.CrossRefGoogle Scholar
and (1964). Random walk models for the spike activity of a single neuron. Biophys J 71:41–68.CrossRefGoogle Scholar
, , and (2000). Encoding of tactile stimulus location by somatosensory thalamocortical ensembles. J Neurosci 20:3761–3775.CrossRefGoogle ScholarPubMed
, , , and (1997). Toward a neurobiology of temporal cognition: advances and challenges. Curr Opin Neurobiol 7:170–184.CrossRefGoogle Scholar
, , , and (1989). Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338:334–337.CrossRefGoogle ScholarPubMed
, , , et al. (2002). Spike train dynamics predicts theta-related phase precession in hippocampal pyramidal cells. Nature 417:738–741.CrossRefGoogle ScholarPubMed
, , , , and (2003). Organization of cell assemblies in the hippocampus. Nature 424:552–556.CrossRefGoogle ScholarPubMed
and (2004). Temporal dynamics of shape analysis in macaque visual area V2. J Neurophysiol 92:3030–3042.CrossRefGoogle ScholarPubMed
, , , , and (2001). Firing rates of hippocampal neurons are preserved during subsequent sleep episodes and modified by novel awake experience. Proc Natl Acad Sci USA 98:9386–9390.CrossRefGoogle ScholarPubMed
and (2002). Coordinated reactivation of distributed memory traces in primate neocortex. Science 297:2070–2073.CrossRefGoogle ScholarPubMed
(1982). Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci USA 79:2554–2558.CrossRefGoogle ScholarPubMed
, , and (2003). Independent rate and temporal coding in hippocampal pyramidal cells. Nature 425:828–832.CrossRefGoogle ScholarPubMed
, , , et al. (2004). Synfire chains and cortical songs: temporal modules of cortical activity. Science 304:559–564.CrossRefGoogle ScholarPubMed
, , and (2004). Spike-timing dynamics of neuronal groups. CerebCortex 14:933–944.CrossRefGoogle Scholar
, , and (2000). Low response variability in simultaneously recorded retinal, thalamic, and cortical neurons. Neuron 27:635–646.CrossRefGoogle ScholarPubMed
, , and (2001). Dynamic and multimodal responses of gustatory cortical neurons in awake rats. J Neurosci 21:4478–4489.CrossRefGoogle ScholarPubMed
, , and (1999). Reactivation of hippocampal cell assemblies: effects of behavioral state, experience, and EEG dynamics. J Neurosci 19:4090–4101.CrossRefGoogle ScholarPubMed
(1996). Dynamical representation of odors by oscillating and evolving neural assemblies. Trends Neurosci 19:489–496.CrossRefGoogle ScholarPubMed
and (2002). Memory of sequential experience in the hippocampus during slow wave sleep. Neuron 36:1183–1194.CrossRefGoogle ScholarPubMed
and (2001). Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep. Neuron 29:145–156.CrossRefGoogle ScholarPubMed
, , , , and (2007). Sequential structure of neocortical spontaneous activity in vivo. Proc Natl Acad Sci USA 104:347–352.CrossRefGoogle ScholarPubMed
, , , and (2005). Internal dynamics determine the cortical response to thalamic stimulation. Neuron 48:811–823.CrossRefGoogle ScholarPubMed
, , and (1998). Who reads temporal information contained across synchronized and oscillatory spike trains?Nature 395:693–698.CrossRefGoogle ScholarPubMed
and (1997). A synaptically controlled, associative signal for Hebbian plasticity in hippocampal neurons. Science 275:209–213.CrossRefGoogle ScholarPubMed
and (1995). Reliability of spike timing in neocortical neurons. Science 268:1503–1506.CrossRefGoogle ScholarPubMed
, , , , and (2001). Dynamics of spontaneous activity in neocortical slices. Neuron 32:883–898.CrossRefGoogle ScholarPubMed
(1971). Simple memory: a theory for archicortex. Phil Trans R Soc Lond B 262:23–81.CrossRefGoogle ScholarPubMed
, , , et al. (2002). Hippocampal pyramidal cell-interneuron spike transmission is frequency dependent and responsible for place modulation of interneuron discharge. J Neurosci 22:RC197.CrossRefGoogle ScholarPubMed
and (2002). Limits to the temporal fidelity of cortical spike rate signals. Nat Neurosci 5:463–471.CrossRefGoogle ScholarPubMed
, , and (2002). Role of experience and oscillations in transforming a rate code into a temporal code. Nature 417:741–746.CrossRefGoogle ScholarPubMed
, , , and (1994). A panoramic code for sound location by cortical neurons. Science 264:842–844.CrossRefGoogle ScholarPubMed
, , , et al. (2007). Stochastic emergence of repeating cortical motifs in spontaneous membrane potential fluctuations in vivo. Neuron 53:413–425.CrossRefGoogle ScholarPubMed
, , , , and (1999). Replay and time compression of recurring spike sequences in the hippocampus. J Neurosci 19:9497–9507.CrossRefGoogle ScholarPubMed
and (1993). Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3:317–330.CrossRefGoogle ScholarPubMed
and (1987). Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis. J Neurophysiol 57:162–178.CrossRefGoogle ScholarPubMed
, , , and (1998). The ‘Ideal Homunculus': decoding neural population signals. Trends Neurosci 21:259–265.CrossRefGoogle ScholarPubMed
, , , and (1999). Stochastic nature of precisely timed spike patterns in visual system neuronal responses. J Neurophysiol 81:3021–3033.CrossRefGoogle ScholarPubMed
, , , and (2001). Excess synchrony in motor cortical neurons provides redundant direction information with that from coarse temporal measures. J Neurophysiol 86:1700–1716.CrossRefGoogle ScholarPubMed
, , , and (2001). The role of spike timing in the coding of stimulus location in rat somatosensory cortex. Neuron 29:769–777.CrossRefGoogle ScholarPubMed
, , and (2004). Intrinsic and circuit properties favor coincidence detection for decoding oscillatory input. J Neurosci 24:6037–6047.CrossRefGoogle ScholarPubMed
, , , et al. (1998). Spatiotemporal structure of cortical activity: properties and behavioral relevance. J Neurophysiol 79:2857–2874.CrossRefGoogle ScholarPubMed
, , , and (1997). Spike synchronization and rate modulation differentially involved in motor cortical function. Science 278:1950–1953.CrossRefGoogle ScholarPubMed
, , , , and (2002). Neuronal correlates of decision-making in secondary somatosensory cortex. Nat Neurosci 5:1217–1225.CrossRefGoogle ScholarPubMed
and (1998). The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J Neurosci 18:3870–3896.CrossRefGoogle ScholarPubMed
(1993). Synchronization of cortical activity and its putative role in information processing and learning. Annu Rev Physiol 55:349–374.CrossRefGoogle Scholar
and (1996). Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience. Science 271:1870–1873.CrossRefGoogle ScholarPubMed
, , , and (1996). Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences. Hippocampus 6:149–172.3.0.CO;2-K>CrossRefGoogle ScholarPubMed
(1938). The Behavior of Organisms: An Experimental Analysis. New York: Appleton-Century.Google Scholar
and (1993). The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J Neurosci 13:334–350.CrossRefGoogle ScholarPubMed
and (1992). Perforated patch-clamp analysis of the passive membrane properties of three classes of hippocampal neurons. J Neurophysiol 67:508–529.CrossRefGoogle ScholarPubMed
and (1998). Input synchrony and the irregular firing of cortical neurons. Nat Neurosci 1:210–217.CrossRefGoogle ScholarPubMed
, , , and (1997). Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390:70–74.Google ScholarPubMed
, and (2003). Intensity versus identity coding in an olfactory system. Neuron 39:991–1004.CrossRefGoogle Scholar
(1989). Fractal character of the auditory neural spike train. IEEE Trans Biomed Eng 36:150–160.CrossRefGoogle ScholarPubMed
and (1999). Synchronous activity in the visual system. Annu Rev Physiol 61:435–456.CrossRefGoogle ScholarPubMed
, , , et al. (1995). Dynamics of neuronal interactions in monkey cortex in relation to behavioural events. Nature 373:515–518.CrossRefGoogle ScholarPubMed
, , and (2000). Top–down processing mediated by interareal synchronization. Proc Natl Acad Sci USA 97:14 748–14 753.CrossRefGoogle Scholar
and (1997). GABAergic modulation of hippocampal population activity: sequence learning, place field development, and the phase precession effect. J Neurophysiol 78:393–408.CrossRefGoogle ScholarPubMed
and (2003). Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426:442–446.CrossRefGoogle ScholarPubMed
and (1994). Reactivation of hippocampal ensemble memories during sleep. Science 265:676–679.CrossRefGoogle ScholarPubMed
, , and (2000). Hippocampal neurons encode information about different types of memory episodes occurring in the same location. Neuron 27:623–633.CrossRefGoogle ScholarPubMed
Accessibility standard: Unknown
Why this information is here
This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.Accessibility Information
Accessibility compliance for the PDF of this chapter is currently unknown
and may be updated in the future.