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Neural Clock

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Brodmann area - highlighting the entorhinal cortex

Neural clock is the part of the brain that is responsible as the 'time keeper' for recording memories and experience as they are perceived in small scales. Observations of the lateral entorhinal cortex (LEC) in the hippocampus of the brain during an experience suggests that this region tracks the timespan or duration of an event up to a precise 10 seconds. The actual timescale that is used by the brain to log our memories and experiences, is still not known. [1]

A team of neuroscientist at the Norwegian University of Science and Technology’s Kavli Institute for Systems Neuroscience, led by Albert Tsao has discovered that a part of the lateral entorhinal cortex forms a neural clock network which encodes the experiences and memories perceived as sequences of events. In a paper titled, “Integrating time from experience in the lateral entorhinal cortex” in Nature in 2018[2], Tsao and his team observed a time-coding signal from the brain but could not identify it's pattern. Later on, the team of researchers inferred that the lack of pattern was due to the signal fluctuating according to the passage of time hence the lack of an apparent pattern.[3] This gave the notion that the memories and experiences are perceived as an "episodic time".[4]

Thesis

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The encoding of the episodic memory in the hippocampus has shown the need for a constitute that could be used as a timescale[5]. However, even with an extensive amount of work being carried out to discern the role of the hippocampus in generating a time-code signal,[6][7][8] knowledge on how this signal represents time in the encoding of episodic memory is still is the budding stage of research. With the knowledge that this episodic memory/episodic time being used by the brain to arrange our experiences, the team at Kavli Institute were able to deduce that the time coding signal that they were looking for needed not be of standard, precise time measurement like second and milliseconds.[2] This would then differentiate this new neural time signal when compared to the clocks in the brain that we already know of; the interval and the circadian clocks.[9][10][11] The neural time code signal they were looking for they decided needed to fulfill two critical criteria that could prove that experiences we perceive are time-encoded into episodic memory:

  • The neural code should be generated naturally without a dedicated stimulus. For example: behavioral training. This was deemed fundamental as the capturing of the time coded signal should support the encoding of episodic memory as the experience is processed by the brain.[2]
  • The neural code should be able to encode different timescales. As it is established that experience recorded as memory can seem to occur at differentiated time frames, (for example: the oddball effect) it is necessary for this time code signal to encompass and encode those memory as well.[2]
Place cells that encode spatial memory located in the medial entorhinal cortex.

Another purpose for this research lay behind a previously run study that found two types of time signals in the hippocampus and the medial entorhinal cortex (MEC):

  • They found sparse clusters of cells that generate this signal and dubbed it ‘time-cells’. These cells were observed to fire at selected points in time when the test animals performed their task. Primarily at the beginning of the task.[12][5]
  • The other representation of time was observed by the disassociation of the ‘place cells’ (that was being researched in that particular study) from days to hours.[13][14]

Though seemed promising, both these time signals were perceived to be too erratic and random in nature at that time.[15][16] This further meant that these time signals were not suitable to represent the time for complete cycles of episodic memory encoding. The study conducted by Tsao et al. focused in researching time coding signal outside of the place-cell system, mainly in the lateral entorhinal cortex (LEC). This area of the entorhinal cortex was mainly chosen because of the three reasons:

  1. The LEC is involved in a major part of cortical input and memory encoding to the hippocampus,[2]
  2. As discovered by the previous study on place-cells in the MEC, LEC exhibited unstable temporal responses when the physical stimuli were presented,[2]
  3. A definitive, main function for the LEC has not been further established to date.[2]

Research

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The research to discern the time-coding signal originating from the LEC were carried out on lab rats running task in a box with alternating black and with walls and also with cue cards. The measurements for the temporal signal were recorded from the LEC, CA3 and MEC as well for comparison.[2][17]

LEC’s individual cell time coding

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To begin the research off the research team worked on finding responses in individual LEC cells by capturing the individual neuron firing rate and plotting the data obtained using a generalized linear model (GLM). Using the alternate wall color and the spatial position as a comparable variable to the neuronal activity, the team were able to see a relative increase in activity in all LEC, CA3 and MEC.[18] Due to GLM’s feature of modelling time as a linearly increasing function, the suggested ‘time-cells’ around the entorhinal/hippocampal circuit show some ramping activity;[2][19] both in deep and apparent layers of the cortex.

Hippocampal formation with the LEC, MEC, CA1 & CA3 areas that are actively recorded for temporal signal.

LEC’s population state time coding

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Looking towards the larger population of LEC cells to find the robust correlation of temporal signals, the team used a linear discriminant analysis on all the population data from individual test subjects. They were looking to enumerate the temporal data obtained and train a linear multiclass support vector machine to find the time periods.[18][2] This showed a very precise time period difference all around the black and white experiment. An increase in temporal signal was also observed in the LEC. Although the CA3 and the MEC did show activity as well. The time coding signal in the LEC was witnessed to be unique in the LEC and much more substantial. The team were then able to infer that the population state activity in the LEC defined a unique timescale context for every time period measured on the scale of minutes.[5][2] The experiment was replicated again, recording the time period difference across the entorhinal system and CA subfields. The result showed that the LEC gave a more prominent activity reading with the need for fewer cells to reach higher decoding accuracy.[2]

Temporal signal generates intrinsically

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Tsao and his team wanted to realize how this temporal coding arises from the LEC. The two theorized idea was a) the ‘explicit mechanism’, in which the LEC works exactly like a clock ticking consistently and forging stamps of consistent time for experiences perceived or b) the ‘inherent mechanism’, in which a temporal signal in thought to arise from the brain experiencing moment-to-moment events.[20][21][2] The ‘inherent mechanism’ also suggests that this free-flowing, continuous change of experience gives rise to a unique neural activity that can be recorded as temporal responses. The experiment was set with the animals performing continuous repetitive task and a comparison study where the animals were foraging freely. The results show that as the test subjects repeated the tasks consistently the mean accuracy faltered over time as opposed to free-foraging test subjects. This indicated that the time signal which rises from the LEC does not copy an explicit clock but mirrors the intricacy of experiences being perceived.[2][22]

Analysis

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The effort of this research that was carried out by the team at Kavli brought to light on the ability of the brain to recall the time-specific details of past experiences is an essential element in the encoding of the episodic memory. Based on the research that was conducted, the unique time-coding signal in the LEC encodes time as memories for multiple scales; from seconds to hours depending on the experience that is being perceived.[2] It was also noted that this neural coding just usually marks the progression of free-flowing time, encoding duration and temporally structuring experiences. However, as observed by the task experiment ran with the animals, this neural coding takes the role of a stopwatch that encodes time relative to environment and the experience that is being perceived throughout the task. This therefore gave further endorsement that this temporal coding was particularly well-suited for temporal encoding of episodic memory and it clearly distinguishes itself from the previously devised interval-timing mechanisms.[23][24]

In addition, the results also support recent works that devised temporal signals can be intrinsically[22] generated as a result of external and internal stimulated inputs.[25][26] This observation was made when the time coding signal corroborated different points of temporal reference using varying high-dimensional population states. These high-dimensional states, differentiated at downstream readouts, was deduced to be produced by the LEC by an amalgam of the recurrent local LEC connectivity[27] and the uniquely diverse set of input that the LEC gets.[28] Another key observation that was pointed out was the anatomical positioning of the LEC; making it a portal for responses being transferred to the hippocampus. This brought forward the theory that temporal representations outside the entorhinal/hippocampal system would come together in the LEC to form a unified time coding signal that encodes episodic memories.[29] In relation to this, as a final step it was theorized that this temporal coded episodic memory would in turn integrate with space-coding signal from the MEC to form a robust memory of ‘what-when-where’ in the hippocampus.[5][2]

See also

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References

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  1. ^ FeaturedNeuroscience·August 29; 2018 (2018-08-29). "How the Brain Experiences Time". Neuroscience News. Retrieved 2020-10-11. {{cite web}}: |last2= has numeric name (help)CS1 maint: numeric names: authors list (link)
  2. ^ a b c d e f g h i j k l m n o p Tsao, Albert; Sugar, Jørgen; Lu, Li; Wang, Cheng; Knierim, James J.; Moser, May-Britt; Moser, Edvard I. (2018-09). "Integrating time from experience in the lateral entorhinal cortex". Nature. 561 (7721): 57–62. doi:10.1038/s41586-018-0459-6. ISSN 1476-4687. {{cite journal}}: Check date values in: |date= (help)
  3. ^ "Scientists discover a "neural clock" deep inside the human brain". Big Think. 2018-08-30. Retrieved 2020-10-11.
  4. ^ "Neuroscience Discovers the Brain's Neural Clock". Psychology Today. Retrieved 2020-10-11.
  5. ^ a b c d "On the Integration of Space, Time, and Memory". Neuron. 95 (5): 1007–1018. 2017-08-30. doi:10.1016/j.neuron.2017.06.036. ISSN 0896-6273.
  6. ^ Fortin, Norbert J.; Agster, Kara L.; Eichenbaum, Howard B. (2002-03-25). "Critical role of the hippocampus in memory for sequences of events". Nature Neuroscience. 5 (5): 458–462. doi:10.1038/nn834. ISSN 1097-6256.
  7. ^ Lehn, H.; Steffenach, H.-A.; van Strien, N. M.; Veltman, D. J.; Witter, M. P.; Haberg, A. K. (2009-03-18). "A Specific Role of the Human Hippocampus in Recall of Temporal Sequences". Journal of Neuroscience. 29 (11): 3475–3484. doi:10.1523/jneurosci.5370-08.2009. ISSN 0270-6474.
  8. ^ Hsieh, Liang-Tien; Gruber, Matthias J.; Jenkins, Lucas J.; Ranganath, Charan (2014-03-05). "Hippocampal Activity Patterns Carry Information about Objects in Temporal Context". Neuron. 81 (5): 1165–1178. doi:10.1016/j.neuron.2014.01.015. ISSN 0896-6273. PMC 3984944. PMID 24607234.
  9. ^ Ferbinteanu, Janina; Kennedy, Pamela J.; Shapiro, Matthew L. (2006). "Episodic memory—From brain to mind". Hippocampus. 16 (9): 691–703. doi:10.1002/hipo.20204. ISSN 1050-9631.
  10. ^ Buzsáki, György; Llinás, Rodolfo (2017-10-26). "Space and time in the brain". Science. 358 (6362): 482–485. doi:10.1126/science.aan8869. ISSN 0036-8075.
  11. ^ Hassabis, Demis; Maguire, Eleanor A. (2007-07). "Deconstructing episodic memory with construction". Trends in Cognitive Sciences. 11 (7): 299–306. doi:10.1016/j.tics.2007.05.001. ISSN 1364-6613. {{cite journal}}: Check date values in: |date= (help)
  12. ^ Eichenbaum, Howard (2014-11). "Time cells in the hippocampus: a new dimension for mapping memories". Nature reviews. Neuroscience. 15 (11): 732–744. doi:10.1038/nrn3827. ISSN 1471-003X. PMC 4348090. PMID 25269553. {{cite journal}}: Check date values in: |date= (help)
  13. ^ Kraus, Benjamin J.; Brandon, Mark P.; Robinson, Robert J.; Connerney, Michael A.; Hasselmo, Michael E.; Eichenbaum, Howard (2015-11-04). "During running in place, grid cells integrate elapsed time and distance run". Neuron. 88 (3): 578–589. doi:10.1016/j.neuron.2015.09.031. ISSN 0896-6273. PMC 4635558. PMID 26539893.
  14. ^ Mankin, Emily A.; Diehl, Geoffrey W.; Sparks, Fraser T.; Leutgeb, Stefan; Leutgeb, Jill K. (2015-01-07). "Hippocampal CA2 activity patterns change over time to a larger extent than between spatial contexts". Neuron. 85 (1): 190–201. doi:10.1016/j.neuron.2014.12.001. ISSN 1097-4199. PMC 4392894. PMID 25569350.
  15. ^ Hargreaves, E. L. (2005-06-17). "Major Dissociation Between Medial and Lateral Entorhinal Input to Dorsal Hippocampus". Science. 308 (5729): 1792–1794. doi:10.1126/science.1110449. ISSN 0036-8075.
  16. ^ Deshmukh, Sachin S.; Knierim, James J. (2011). "Representation of Non-Spatial and Spatial Information in the Lateral Entorhinal Cortex". Frontiers in Behavioral Neuroscience. 5. doi:10.3389/fnbeh.2011.00069. ISSN 1662-5153.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  17. ^ Hargreaves, Eric L.; Rao, Geeta; Lee, Inah; Knierim, James J. (2005-06-17). "Major dissociation between medial and lateral entorhinal input to dorsal hippocampus". Science (New York, N.Y.). 308 (5729): 1792–1794. doi:10.1126/science.1110449. ISSN 1095-9203. PMID 15961670.
  18. ^ a b Keene, Christopher S.; Bladon, John; McKenzie, Sam; Liu, Cindy D.; O'Keefe, Joseph; Eichenbaum, Howard (2016-03-30). "Complementary Functional Organization of Neuronal Activity Patterns in the Perirhinal, Lateral Entorhinal, and Medial Entorhinal Cortices". The Journal of Neuroscience. 36 (13): 3660–3675. doi:10.1523/jneurosci.4368-15.2016. ISSN 0270-6474.
  19. ^ Schoenbaum, Geoffrey, ed. (2017-06-13). "Decision letter: Phasic and tonic neuron ensemble codes for stimulus-environment conjunctions in the lateral entorhinal cortex". doi:10.7554/elife.28611.018. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: unflagged free DOI (link)
  20. ^ Buzsáki, György; Llinás, Rodolfo (2017-10-26). "Space and time in the brain". Science. 358 (6362): 482–485. doi:10.1126/science.aan8869. ISSN 0036-8075.
  21. ^ Buonomano, Dean V.; Maass, Wolfgang (2009-01-15). "State-dependent computations: spatiotemporal processing in cortical networks". Nature Reviews Neuroscience. 10 (2): 113–125. doi:10.1038/nrn2558. ISSN 1471-003X.
  22. ^ a b "Breakthrough: How the brain keeps track of time". sciencenorway.no (in Norwegian). 2018-09-04. Retrieved 2020-11-30.
  23. ^ Finnerty, G. T.; Shadlen, M. N.; Jazayeri, M.; Nobre, A. C.; Buonomano, D. V. (2015-10-14). "Time in Cortical Circuits". Journal of Neuroscience. 35 (41): 13912–13916. doi:10.1523/jneurosci.2654-15.2015. ISSN 0270-6474.
  24. ^ Mauk, Michael D.; Buonomano, Dean V. (2004-07-21). "THE NEURAL BASIS OF TEMPORAL PROCESSING". Annual Review of Neuroscience. 27 (1): 307–340. doi:10.1146/annurev.neuro.27.070203.144247. ISSN 0147-006X.
  25. ^ Howard, Marc W.; MacDonald, Christopher J.; Tiganj, Zoran; Shankar, Karthik H.; Du, Qian; Hasselmo, Michael E.; Eichenbaum, Howard (2014-03-26). "A Unified Mathematical Framework for Coding Time, Space, and Sequences in the Hippocampal Region". Journal of Neuroscience. 34 (13): 4692–4707. doi:10.1523/JNEUROSCI.5808-12.2014. ISSN 0270-6474. PMID 24672015.
  26. ^ Buonomano, Dean V.; Maass, Wolfgang (2009-01-15). "State-dependent computations: spatiotemporal processing in cortical networks". Nature Reviews Neuroscience. 10 (2): 113–125. doi:10.1038/nrn2558. ISSN 1471-003X.
  27. ^ Dolorfo, C. L.; Amaral, D. G. (1998-08-17). "Entorhinal cortex of the rat: organization of intrinsic connections". The Journal of Comparative Neurology. 398 (1): 49–82. doi:10.1002/(sici)1096-9861(19980817)398:13.0.co;2-9. ISSN 0021-9967. PMID 9703027.
  28. ^ Bota, Mihail; Sporns, Olaf; Swanson, Larry W. (2015-04-06). "Architecture of the cerebral cortical association connectome underlying cognition". Proceedings of the National Academy of Sciences. 112 (16): E2093–E2101. doi:10.1073/pnas.1504394112. ISSN 0027-8424.
  29. ^ Igarashi, Kei M.; Lu, Li; Colgin, Laura L.; Moser, May-Britt; Moser, Edvard I. (2014-06). "Coordination of entorhinal–hippocampal ensemble activity during associative learning". Nature. 510 (7503): 143–147. doi:10.1038/nature13162. ISSN 1476-4687. {{cite journal}}: Check date values in: |date= (help)
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