This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/28433 in citations.
Significant Spatio-Temporal Spike Patterns in Macaque Monkey Motor Cortex
Significant Spatio-Temporal Spike Patterns in Macaque Monkey Motor Cortex
The cell assembly hypothesis [1] postulates that neurons coordinate their activity through the formation and repetitive co-activation of groups. While the classical theory of neural coding revolves around the concept that information is encoded in firing rates, we assume that assembly activity is e...
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Personal Name(s): | Stella, Alessandra (Corresponding author) |
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Bouss, Peter / Palm, Günther / Riehle, Alexa / brochier, thomas / Grün, Sonja | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
Imprint: |
2021
|
Conference: | Neural Coding 2021, Online (Germany), 2021-07-26 - 2021-07-29 |
Document Type: |
Conference Presentation |
Research Program: |
Human Brain Project Specific Grant Agreement 2 Helmholtz Analytics Framework Neuroscientific Foundations Connectivity and Activity Computational Principles Human Brain Project Specific Grant Agreement 3 |
Link: |
OpenAccess |
Publikationsportal JuSER |
The cell assembly hypothesis [1] postulates that neurons coordinate their activity through the formation and repetitive co-activation of groups. While the classical theory of neural coding revolves around the concept that information is encoded in firing rates, we assume that assembly activity is expressed by the occurrence of precisely timed spatio-temporal patterns (STPs) of spikes emitted by neurons that are members of the assembly, e.g. a synfire chain. We focus on a method that is capable of detecting significant STPs in parallel spike trains, called SPADE [2,3,4]. SPADE first identifies repeating STPs using Frequent Itemset Mining [5], and then evaluates the detected patterns for significance through comparison to patterns found in surrogate data. Various surrogate techniques can be used to evaluate significance, and their correct choice is crucial to ensure that by-chance patterns are not classified as significant [6]. The final step of the method is the removal of false positive patterns being a by-product of true patterns with background activity. Here we first evaluate how different six types of surrogate techniques affect the results of SPADE, in terms of the general statistics of the generated surrogates, and in terms of the amount of false positives. We conclude that spike-train shifting [7] is the preferable choice for our type of data, which typically show a CV < 1 and have a dead time after the spikes of 1.6/1.2ms induced by the spike sorter (Plexon). Uniform dithering, in contrast, leads to a high false positive rate.In a next step, we evaluate if cell assemblies are active in relation to motor behavior [2]. Therefore, we analyze 20 experimental sessions, each of about 15min recording, consisting of parallel spike data recorded by a 10x10 electrode Utah array in the pre-/motor cortex of two macaque monkeys performing a reach-to-grasp task [8, 9]. The monkeys have four possible behavioral conditions of grasping and pulling an object consisting of combinations of two possible grip types (precision or side grip) and two different amounts of force required to pull the object (low or high). We segment each session into 6 periods of 500ms duration and analyze them independently for the occurrence of STPs. Each significant STP is identified by its neuron composition, its number and times of occurrences and the delays between spikes.We find that significant STPs indeed occur in all phases of the behavior. Their size ranges between 2 and 6 neurons, and their maximal spatial extent is 60ms. The STPs are specific to the behavioral context, i.e. within the different trial epochs and across conditions (different grip and force type combinations). This suggests that different assemblies are active in the context of different behavior. Within a recording session, we typically find one neuron that is involved in all STPs. The neurons involved in STPs within a session are not clustered on the Utah array, but may be far apart. We further plan to investigate the spatial arrangement of the patterns on the Utah array, to determine whether there are preferred spatial directions of pattern spike sequences, as found in [2] for synchronous patterns. Finally, we plan to investigate whether the grip type can be better decoded on the basis of the type of STPs or by using the firing rates of the neurons. References[1] Hebb, D. O. (1949). John Wiley & Sons[2] Torre et al (2016) J Neurosci 36:8329–8340. DOI: 10.1523/JNEUROSCI.4375-15.2016.[3] Quaglio et al. (2017). Front Comp Neurosci, 11:41. DOI: 10.3389/fncom.2017.00041[4] Stella et al. (2019). Biosystems, [5] Pormann et al. (2021). Submitted[6] Stella et al. (2021). In preparation[7] Pipa et al. (2013) [8] Brochier et al. (2018). Scientific data, 5, 180055. DOI: 10.1038/sdata.2018.55[9] Riehle et al. (2013) |