Skip to main content
Log in

Characteristics of the Neuronal Support for Operative Behavior Formed by Mono- and Multistep Methods

  • Published:
Neuroscience and Behavioral Physiology Aims and scope Submit manuscript

We report here studies to determine whether, and if so, how, the neuronal support for behavior depends on the number of training steps presented in the history of its formation. A training step is the formation of a new skill consisting of a sequence of behavioral acts whose execution leads to achievement of a result: receipt of food. Rats (Long Evans) were trained to an operant pedal-pressing food-procuring skill using two methods – with one or several stages – and the activity of individual neurons in the retrosplenial dysgranular area of the cortex was recorded. In the group of rats in which the skill was acquired in four steps (multistep), there were significantly more neurons specialized for approach and pedal-pressing (consistently activated during these acts) and the mean firing frequency of neurons with structured but not necessarily consistent activity in the learned behavior was greater; there were also more clusters combining cells with selectively increased activity in the same sets of behavioral acts. In animals trained in a single step, only two neurons specialized for approach and pedal-pressing were seen, though there were more cells with structured activity in behavior, these cells displaying maximum firing frequencies in these acts. Thus, the different number of stages in the history of learning the same operant skill was linked with significant differences in the relative number and pattern of activity of two categories of retrosplenial cortex (RC) neurons: those specialized relative to the acts of the learned behavior and cells with structured but variable activity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Aleksandrov, I. O. and Maksimova, N. E., “The process of differentiation: the content of the concept and the potential for operationalization in psychological studies,” in: A Differential-Integrational Theory of Development, LRC Publishing House [Languages of Slavic Culture], Znak, Moscow (2014), pp. 87–138.

  • Aleksandrov, I. O., Maksimova, N. E., Gorkin, A. G., et al., “A set of studies of the structure of individual knowledge,” Psikhol. Zh., 20, No. 1, 49–69 (1999).

    Google Scholar 

  • Aleksandrov, Yu. I., “Cognition as systemogenesis,” in: Anticipation: Learning from the Past. The Russian/Soviet Contributions to the Science of Anticipation, Berlin (2015), pp. 193–221.

  • Aleksandrov, Yu. I., “Constancy of the composition of activated neurons on changes in the parameters of targeted movements,” Zh. Vyssh. Nerv. Deyat., 32, No. 2, 333–335 (1982).

    Google Scholar 

  • Aleksandrov, Yu. I., “How we fragment the world: the view from inside versus the view from outside,” Soc. Sci. Inform., Spec. Iss., Cognit. Technol., 47, No. 3, 419–457 (2008).

    Google Scholar 

  • Aleksandrov, Yu. I., “Learning and memory: traditional and systems approaches,” Neurosci. Behav. Physiol., 36, No. 9, 969–985 (2006).

    PubMed  Google Scholar 

  • Aleksandrov, Yu. I., Gorkin, A. G., Sozinov, A. A., et al., “Memory consolidation and reconsolidation: a psychophysiological analysis,” Vopr. Psikhol., 3, 1–13 (2015).

    Google Scholar 

  • Aleksandrov, Yu. I., Grechenko, T. N., Gavrilov, V. V., et al., “Patterns of formation and realization of individual experience,” Zh. Vyssh. Nerv. Deyat., 47, No. 2, 243–260 (1997).

    Google Scholar 

  • Aleksandrov, Yu. I., Grinchenko, Yu. V., Laukka, S., et al., “Effect of ethanol on hippocampal neurons depends on their behavioral specialization,” Acta Physiol. Scand., 149, 105–115 (1993).

    Google Scholar 

  • Alexander, A. S. and Nitz, D. A., “Retrosplenial cortex maps the conjunction of internal and external spaces,” Nat. Neurosci., 18, 1143–1151 (2015).

    CAS  PubMed  Google Scholar 

  • Alexander, A. S. and Nitz, D. A., “Spatially periodic activation patterns of retrosplenial cortex encode route sub-spaces and distance traveled,” Curr. Biol., 27, 1551–1560 (2017).

    CAS  PubMed  Google Scholar 

  • Alexandrov, Y. I., Sozinov, A. A., Svarnik, O. E., et al., “Neuronal bases of systemic organization of behavior,” in: Systems Neuroscience, Cheung-Hoi, Yu, A. and Li, L. (eds.), Advances in Neurobiology, Vol. 21, Springer (2018).

  • Ardid, S., Vinck, M., Kaping, D., et al., “Mapping of functionally characterized cell classes onto canonical circuit operations in primate prefrontal cortex,” J. Neurosci., 35, 2975–2991 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Arutyunova, K. R., Gavrilov, V. V., and Aleksandrov, Yu. I., “Learning and behavior in the absence of visual contact with the environment in rats,” Eksperim. Psikhol., 7, No. 3, 31–43 (2014).

    Google Scholar 

  • Auger, S. D. and Maguire, E. A., “Retrosplenial cortex indexes stability beyond the spatial domain,” J. Neurosci., 38, No. 6, 1472–1481 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bobrovnikov, L. V., “Probabilistic-statistical criteria for assessment of behavioral specialization of nerve cells,” Zh. Vyssh. Nerv. Deyat., 10, No. 2, 90–98 (1989).

    Google Scholar 

  • Buzsáki G., “Neural syntax: cell assemblies, synapsembles and readers,” Neuron, 68, No. 3, 362–385 (2010).

    PubMed  PubMed Central  Google Scholar 

  • Chen, L. L., Lin, L. H., Barnes, C. A., and McNaughton, B. L., “Headdirection cells in the rat posterior cortex,” Exp. Brain Res., 101, 8–23 (1994).

    CAS  PubMed  Google Scholar 

  • Cho, J. and Sharp, P. E., “Head direction, place, and movement correlates for cells in the rat retrosplenial cortex,” Behav. Neurosci., 115, 3–25 (2001).

    CAS  PubMed  Google Scholar 

  • Clopath, C., Bonhoeffer, T., Hübener, M., and Rose, T., “Variance and invariance of neuronal long-term representations,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 372, No. 1715, 20160161 (2017).

  • Czajkowski, R., Jayaprakash, B., Wiltgen, B., et al., “Encoding and storage of spatial information in the retrosplenial cortex,” Proc. Natl. Acad. Sci. USA, 111, No. 23, 8661–8666 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Deolindo, C. S., Kunicki, A. C. B., da Silva, M. I., et al., “Neuronal assemblies evidence distributed interactions within a tactile discrimination task in rats,” Front. Neural Circ., 11, 114 (2017).

    Google Scholar 

  • Durstewitz, D., Vittoz, N. M., Floresco, S. B., and Seamans, J. K., “Abrupt transitions between prefrontal neural ensemble states accompany behavioral transitions during rule learning,” Neuron, 66, 438–448 (2010).

    CAS  PubMed  Google Scholar 

  • Euston, D. R. and McNaughton, B. L., “Apparent encoding of sequential context in rat medial prefrontal cortex is accounted for by behavioral variability,” J. Neurosci., 26, 13,143–13,155 (2006).

    Google Scholar 

  • Frank, L. M., Brown, E. N., and Wilson, M. A., “A comparison of the firing properties of putative excitatory and inhibitory neurons from CA1 and the entorhinal cortex,” J. Neurophysiol., 86, No. 4, 2029–2040 (2001).

    CAS  PubMed  Google Scholar 

  • Fujisawa, S., Amarasingham, A., Harrison, M. T., and Buzsáki G., “Behaviordependent short-term assembly dynamics in the medial prefrontal cortex,” Nat. Neurosci., 11, No. 7, 823–833 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gavrilov, V. V., “Formation of individual experience with and without the aid of the experimenter and on observation of the behavior of others,” in: Human Psychology in the Current World, Zhuravlev, A. L. et al. (eds.), Moscow (2009), pp, 329–332.

  • Gholamrezaei, G. and Whishaw, I. Q., “Individual differences in skilled reaching for food related to increased number of gestures: evidence for goal and habit learning of skilled reaching,” Behav. Neurosci., 123, No. 4, 863–74 (2009).

    PubMed  Google Scholar 

  • Gorkin, A. G. and Kuzina, E. A., “Correlation of the differentiation of neuron activity in the retrosplenial cortex and measures of operant behavior,” Neirokomp’yutery, 8, 35–36 (2017).

    Google Scholar 

  • Gorkin, A. G. and Shevchenko, D. G., “Differences in the activity of neurons in the rabbit limbic cortex in different learning strategies,” Zh. Vyssh. Nerv. Deyat. 45, No. 1, 90–100 (1995).

    CAS  Google Scholar 

  • Gorkin, A. G., “Behavioral specialization of cortical neurons at different steps of training,” in: The EEG and Neuron Activity in Psychophysiological Studies, Nauka, Moscow (1987), pp. 73–80.

  • Gorkin, A. G., Kuzina, E. A., Ivlieva, N. P., et al., “Patterns of neuron activity in the retrosplenial area of the cortex in operant food-procuring behavior in rats of different ages,” Zh. Vyssh. Nerv. Deyat., 67, No. 3, 1–7 (2017).

    Google Scholar 

  • Greenberg, P. A. and Wilson, F. A., “Functional stability of dorsolateral prefrontal neurons,” J. Neurophysiol., 92, 1042–1055 (2004).

    PubMed  Google Scholar 

  • Hayden, B. Y., Smith, D. V., and Platt, M. L., “Electrophysiological correlates of default-mode processing in macaque posterior cingulate cortex,” Proc. Natl. Acad. Sci. USA, 106, No. 14, 5948–5953 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hok, V., Chah, E., Reilly, R. B., and O’Mara, S. M., “Hippocampal dynamics predict interindividual cognitive differences in rats,” J. Neurosci., 32, 3540–3551 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hyman, J. M., Ma, L., Balaguer-Ballester, E., et al., “Contextual encoding by ensembles of medial prefrontal cortex neurons,” Proc. Natl. Acad. Sci. USA, 109, No. 13, 5086–5091 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Insel, N. and Barnes, C. A., “Differential activation of fast-spiking and regular-firing neuron populations during movement and reward in the dorsal medial frontal cortex,” Cereb. Cortex, 25, No. 9, 2631–2647 (2015), doi: https://doi.org/10.1093/cercor/bhu062.

    Article  PubMed  Google Scholar 

  • Ison, M. J., Mormann, F., Cerf, M., et al., “Selectivity of pyramidal cells and interneurons in the human medial temporal lobe,” J. Neurophysiol., 106, No. 4, 1713–21 (2011).

    PubMed  PubMed Central  Google Scholar 

  • Jacob, P. Y., Casali, G., Spieser, L., et al., “An independent, landmark-dominated head-direction signal in dysgranular retrosplenial cortex,” Nat. Neurosci., 20, No. 2, 173–175 (2016).

    PubMed  PubMed Central  Google Scholar 

  • Korshunov, V. A., “Miniature microdrive for extracellular recording of neuronal activity in freely moving animals,” J. Neurosci. Meth., 57, No. 1, 77–80 (1995).

    CAS  Google Scholar 

  • Lütcke, H., Margolis, D. J., and Helmchen F., “Steady or changing? Longterm monitoring of neuronal population activity,” Trends Neurosci., 36, 375–384 (2013).

    PubMed  Google Scholar 

  • Ma, L., Hyman, J. M., Durstewitz, D., et al., “A quantitative analysis of context-dependent remapping of medial frontal cortex neurons and ensembles,” J. Neurosci., 36, 8258–8272 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ma, L., Hyman, J. M., Lindsay, A. J., et al., “Differences in the emergent coding properties of cortical and striatal ensembles,” Nature Neurosci., 17, No. 8, 1100–1106 (2014).

    CAS  PubMed  Google Scholar 

  • MacDonald, C. J., Lepage, K. Q., Eden, U. T., and Eichenbaum H., “Hippocampal ‘time cells’ bridge the gap in memory for discontiguous events,” Neuron, 71, No. 4, 737–749 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Malagon-Vina, H., Ciocchi, S., Passecker, J., et al., “Fluid network dynamics in the prefrontal cortex during multiple strategy switching,” Nat. Commun., 9, 309 (2018).

    PubMed  PubMed Central  Google Scholar 

  • Mankin, E. A., Diehl, G. W., Sparks, F. T., et al., “Hippocampal CA2 activity patterns change over time to a larger extent than between spatial contexts,” Neuron, 85, 190–202 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mao, D., Kandler, S., McNaughton, B. L., and Bonin V., “Sparse orthogonal population representation of spatial context in the retrosplenial cortex,” Nat. Commun., 8, 243 (2017).

    PubMed  PubMed Central  Google Scholar 

  • Martel, G., Blanchard, J., Mons, N., et al., “Dynamic interplays between memory systems depend on practice: The hippocampus is not always the first to provide solution,” Neuroscience, 150, 743–753 (2007).

    CAS  PubMed  Google Scholar 

  • Martiros, N., Burgess, A. A., and Graybiel, A. M., “Inversely active striatal projection neurons and interneurons selectively delimit useful behavioral sequences,” Curr. Biol., 28, No. 4, 560–573 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mashhoori, A., Hashemnia, S., McNaughton, B. L., et al., “Rat anterior cingulate cortex recalls features of remote reward locations after disfavoured reinforcements,” eLife, 7, e29793 (2018).

    PubMed  PubMed Central  Google Scholar 

  • McKenzie, S., Keene, C. S., Farovik, A., et al., “Representation of memories in the cortical-hippocampal system: Results from the application of population similarity analyses,” Neurobiol. Learn. Mem., 134, 178–91 (2016).

    PubMed  Google Scholar 

  • McMahon, D. B. T., Bondar, I. V., Afuwape, O. A. T., et al., “One month in the life of a neuron: longitudinal single-unit electrophysiology in the monkey visual system,” J. Neurophysiol., 112, No. 7, 1748–1762 (2014).

    PubMed  PubMed Central  Google Scholar 

  • Miller, A. M. P., Vedder, L. C., Law, L. M., and Smith, D. M., “Cues, context, and long-term memory: the role of the retrosplenial cortex in spatial cognition,” Front. Hum. Neurosci., 8, 1441 (2014).

    Google Scholar 

  • Morcos, A. S. and Harvey, C. D., “History-dependent variability in population dynamics during evidence accumulation in cortex,” Nat Neurosci., 19, 1672–1681 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Muzzio, I. A., Levita, L., Kulkarni, J., et al., “Attention enhances the retrieval and stability of visuospatial and olfactory representations in the dorsal hippocampus,” PLoS Biol., 7, e1000140 (2009).

    PubMed  PubMed Central  Google Scholar 

  • Nicolelis, M. A., Fanselow, E. E., and Ghazanfar, A. A., “Hebb’s dream: the resurgence of cell assemblies,” Neuron, 19, 219–221 (1997).

    CAS  PubMed  Google Scholar 

  • Nikol’skaya, K. A. and Khonicheva, R. M., “Features of learning in rats in conditions of free choice,” Zh. Vyssh. Nerv. Deyat., 49, No. 3, 664–674 (1999).

    Google Scholar 

  • Paxinos, G. and Watson C., The Rat Brain in Stereotaxic Coordinates Hard Cover Edition, Elsevier, Amsterdam (2005).

    Google Scholar 

  • Pinto, L. and Dan Y., “Cell type-specific activity in prefrontal cortex during goal-directed behavior,” Neuron, 87, No. 2, 437–450 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  • Renart, A. and Machens, C. K., “Variability in neural activity and behavior,” Curr. Opin. Neurobiol., 25, 211–220 (2014).

    CAS  PubMed  Google Scholar 

  • Ruediger, S., Spirig, D., Donato, F., and Caroni P., “Goal-oriented searching mediated by ventral hippocampus early in trial-and-error learning,” Nat. Neurosci., 15, No. 11, 1563–1571 (2012).

    CAS  PubMed  Google Scholar 

  • Shvyrkov, V. B., “System determination of neuron activity in behavior,” Usp. Fiziol. Nauk., 14, No. 1, 45–66 (1983).

    Google Scholar 

  • Shvyrkov, V. B., Introduction to Objective Psychology: Neuronal Basis of the Mind: Selected Works, Publishing House of the Institute of Psychology, Russian Academy of Sciences (2006).

  • Sidorina, V. V., Merzhanova, G. Kh., Kuleshova, E. P., and Zaleshin, A. V., “Cooperative activity of neurons in the visual, frontal, and sensorimotor areas of the cortex and the dorsal striatum on realization of a behavioral program in conditions of strategy selection,” Zh. Vyssh. Nerv. Deyat., 62, No. 2, 185–196 (2012).

    CAS  Google Scholar 

  • Smith, D. M., Barredo, J., and Mizumori, S. J., “Complimentary roles of the hippocampus and retrosplenial cortex in behavioral context discrimination,” Hippocampus, 22, 1121–1133 (2012).

    PubMed  Google Scholar 

  • Snyder, J. S., Clifford, M. A., Jeurling, S. I., and Cameron, H. A., “Complementary activation of hippocampal-cortical subregions and immature neurons following chronic training in single and multiple context versions of the water maze,” Behav. Brain Res., 227, No. 2, 330–339 (2012).

    PubMed  Google Scholar 

  • Sozinov, A. A., Krylov, A. K., and Aleksandrov, Yu. I., “The interference effect in studies of psychological structures,” Eksperim. Psikhol., 6, No. 1, 5–47 (2013).

    Google Scholar 

  • Svarnik, O. E., Bulava, A. I., and Alexandrov, Y. I., “Expression of c-Fos in the rat retrosplenial cortex during instrumental re-learning of appetitive bar-pressing depends on the number of stages of previous training,” Front. Behav. Neurosci., 7, 78 (2013).

  • Tolkunov, B. F., “Neuronal reactions accompanying behavior and the dynamics of neuron activity,” Zh. Vyssh. Nerv. Deyat., 57, No. 6, 753–761 (2007).

    CAS  Google Scholar 

  • Tsao, A., Moser, M. B., and Moser, E. I., “Traces of experience in the lateral entorhinal cortex,” Curr. Biol., 23, No. 5, 399–405 (2013).

    CAS  PubMed  Google Scholar 

  • Vedder, L. C., Miller, A. M. P., Harrison, M. B., and Smith, D. M., “Retrosplenial cortical neurons encode navigational cues, trajectories and reward locations during goal directed navigation,” Cereb. Cortex, 27, No. 7, 3713–3723 (2017).

    PubMed  Google Scholar 

  • Weible, A. P., Rowland, D. C., Pang, R., and Kentros C., “Neural correlates of novel object and novel location recognition behavior in the mouse anterior cingulate cortex,” J. Neurophysiol., 102, 2055–2068 (2009).

    PubMed  Google Scholar 

  • Wirt, R. A. and Hyman, J. M., “Integrating spatial working memory and remote memory: interactions between the medial prefrontal cortex and hippocampus,” Brain Sci., 7, No. 4, 43 (2017).

    PubMed Central  Google Scholar 

  • Yanike, M., Wirth, S., Smith, A. C., et al., “Comparison of associative learning-related signals in the macaque perirhinal cortex and hippocampus,” Cereb. Cortex, 19, No. 5, 1064–78 (2009).

    PubMed  Google Scholar 

  • Ziv, Y., Burns, L. D., Cocker, E. D., et al., “Long-term dynamics of CA1 hippocampal place codes,” Nat. Neurosci., 16, No. 3, 264–266 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to E. A. Kuzina.

Additional information

Translated from Zhurnal Vysshei Nervnoi Deyatel’nosti imeni I. P. Pavlova, Vol. 69, No. 5, pp. 601–617, September–October, 2019.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kuzina, E.A., Aleksandrov, Y.I. Characteristics of the Neuronal Support for Operative Behavior Formed by Mono- and Multistep Methods. Neurosci Behav Physi 50, 710–722 (2020). https://doi.org/10.1007/s11055-020-00959-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11055-020-00959-2

Keywords

Navigation