{"entity": "researcher", "timestamp": "2026-08-20T20:47:13.672Z", "family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "affiliations": ["Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology Stockholm, Stockholm, Sweden. arvkumar@kth.se.", "Science for Life Laboratory, Stockholm, Sweden. arvkumar@kth.se."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3"}}, "publications": [{"entity": "publication", "iuid": "af579a914d8e4da7b25206ddde4b646f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/af579a914d8e4da7b25206ddde4b646f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/af579a914d8e4da7b25206ddde4b646f"}}, "title": "Can we infer excitation-inhibition balance from the spectrum of population activity?", "authors": [{"family": "Chakravarty", "given": "Kingshuk", "initials": "K"}, {"family": "Roy", "given": "Sangheeta", "initials": "S"}, {"family": "Sinha", "given": "Aniruddha", "initials": "A", "orcid": "0000-0002-4679-3806", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/be1a1625bba846a59f3aeeb68f1a88c8.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal article", "published": "2025-12-13", "journal": {"title": "Commun Biol", "issn": "2399-3642", "volume": "9", "issue": "1", "pages": "51", "issn-l": "2399-3642"}, "abstract": "Networks in the brain operate in an excitation-inhibition (EI) balanced state. Altered EI balance underlies aberrant dynamics and impaired information processing. Given its importance, it is crucial to establish non-invasive measures of the EI balance. Previous studies have suggested that relative EI balance can be inferred from the spectrum of the population signals such as Local Field Potentials (LFP), Electroencephalogram (EEG) and Magnetoencephalography (MEG). This idea exploits the fact that in most cases excitatory and inhibitory synapses have quite different time constants. However, it is not clear to what extent spectral slope of population activity is related to the network parameters that define the EI balance e.g. excitatory and inhibitory conductance. To address this question we simulated two different types of recurrent networks and measured spectral slope for a wide range of parameters. Our results show that the slope of the spectrum cannot predict the ratio of excitatory and inhibitory synaptic conductance. Only in a small set of simulations a change in the spectral slope was consistent with the corresponding change in the synaptic weights or inputs to the network. Thus, our results show that we should be careful in interpreting the change in the slope of the population activity spectrum.", "doi": "10.1038/s42003-025-09315-x", "pmid": "41390698", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12795805"}, {"db": "pii", "key": "10.1038/s42003-025-09315-x"}], "notes": [], "created": "2026-08-20T09:25:30.234Z", "modified": "2026-08-20T09:25:30.345Z"}, {"entity": "publication", "iuid": "7c64d52708894e9bae5e9fdd0a485054", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/7c64d52708894e9bae5e9fdd0a485054.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/7c64d52708894e9bae5e9fdd0a485054"}}, "title": "Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints.", "authors": [{"family": "Tsurumi", "given": "Takayuki", "initials": "T"}, {"family": "Kato", "given": "Ayaka", "initials": "A", "orcid": "0000-0002-6306-6600", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5b0c09585b17459a9ef2f9e40436ba81.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}, {"family": "Morita", "given": "Kenji", "initials": "K", "orcid": "0000-0003-2192-4248", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5ed9416994634747b623d754cc02a5c0.json"}}], "type": "journal article", "published": "2025-09-24", "journal": {"title": "Elife", "issn": "2050-084X", "volume": "14", "issn-l": "2050-084X"}, "abstract": "Representation of external and internal states in the brain plays a critical role in enabling suitable behavior. Recent studies suggest that state representation and state value can be simultaneously learned through Temporal-Difference-Reinforcement-Learning (TDRL) and Backpropagation-Through-Time (BPTT) in recurrent neural networks (RNNs) and their readout. However, neural implementation of such learning remains unclear as BPTT requires offline update using transported downstream weights, which is suggested to be biologically implausible. We demonstrate that simple online training of RNNs using TD reward prediction error and random feedback, without additional memory or eligibility trace, can still learn the structure of tasks with cue-reward delay and timing variability. This is because TD learning itself is a solution for temporal credit assignment, and feedback alignment, a mechanism originally proposed for supervised learning, enables gradient approximation without weight transport. Furthermore, we show that biologically constraining downstream weights and random feedback to be non-negative not only preserves learning but may even enhance it because the non-negative constraint ensures loose alignment-allowing the downstream and feedback weights to roughly align from the beginning. These results provide insights into the neural mechanisms underlying the learning of state representation and value, highlighting the potential of random feedback and biological constraints.", "doi": "10.7554/eLife.104101", "pmid": "40991326", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12459954"}, {"db": "pii", "key": "104101"}], "notes": [], "created": "2026-08-20T13:51:06.068Z", "modified": "2026-08-20T13:51:06.217Z"}, {"entity": "publication", "iuid": "dba3851e366e41c1b361de21a46381b3", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/dba3851e366e41c1b361de21a46381b3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/dba3851e366e41c1b361de21a46381b3"}}, "title": "Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints", "authors": [{"family": "Tsurumi", "given": "Takayuki", "initials": "T"}, {"family": "Kato", "given": "Ayaka", "initials": "A", "orcid": "0000-0002-6306-6600", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5b0c09585b17459a9ef2f9e40436ba81.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}, {"family": "Morita", "given": "Kenji", "initials": "K", "orcid": "0000-0003-2192-4248", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5ed9416994634747b623d754cc02a5c0.json"}}], "type": "journal-article", "published": "2025-09-24", "journal": {"issn": "2050-084X", "volume": "14", "title": "Elife", "issn-l": "2050-084X"}, "abstract": null, "doi": "10.7554/elife.104101.4", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:51:11.382Z", "modified": "2026-08-20T13:51:11.410Z"}, {"entity": "publication", "iuid": "f4e7129494c44a94b41c5c3c51389cdb", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f4e7129494c44a94b41c5c3c51389cdb.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f4e7129494c44a94b41c5c3c51389cdb"}}, "title": "Non-equilibrium dynamics of the neocortex in Parkinson\u2019s disease", "authors": [{"family": "Helson", "given": "Pascal", "initials": "P", "orcid": "0000-0002-2877-3705", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0ee66ee661c64a4a89df82afceff2e11.json"}}, {"family": "Benyahiya", "given": "Elias", "initials": "E"}, {"family": "Manikandan", "given": "Sreekanth", "initials": "S"}, {"family": "Waldthaler", "given": "Josefine", "initials": "J"}, {"family": "Vinding", "given": "Mikkel C", "initials": "MC"}, {"family": "Lundqvist", "given": "Daniel", "initials": "D"}, {"family": "Svenningsson", "given": "Per", "initials": "P"}, {"family": "Mitra", "given": "Dhrubaditya", "initials": "D"}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "posted-content", "published": "2025-08-13", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2025.08.09.25333337", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:06:49.877Z", "modified": "2026-08-20T11:06:49.937Z"}, {"entity": "publication", "iuid": "c5d70786407f43ac81fdca0f8fd80285", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/c5d70786407f43ac81fdca0f8fd80285.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/c5d70786407f43ac81fdca0f8fd80285"}}, "title": "How sub-optimal are the neural representations: show me your null model.", "authors": [{"family": "Lenninger", "given": "Movitz", "initials": "M", "orcid": "0000-0002-6165-4900", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/87757488f4ca44e3af4211b5de813ece.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal article", "published": "2025-04-01", "journal": {"title": "J. Neurophysiol.", "issn": "1522-1598", "volume": "133", "issue": "4", "pages": "1083-1085", "issn-l": "0022-3077"}, "abstract": null, "doi": "10.1152/jn.00085.2025", "pmid": "40013533", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T12:03:13.100Z", "modified": "2026-08-20T12:03:13.168Z"}, {"entity": "publication", "iuid": "3a22791bb4c141a68b6b81fb2c7b9c49", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3a22791bb4c141a68b6b81fb2c7b9c49.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3a22791bb4c141a68b6b81fb2c7b9c49"}}, "title": "Can we infer excitation-inhibition balance from the spectrum of population activity?", "authors": [{"family": "Chakravarty", "given": "Kingshuk", "initials": "K"}, {"family": "Roy", "given": "Sangheeta", "initials": "S"}, {"family": "Sinha", "given": "Aniruddha", "initials": "A"}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "posted-content", "published": "2024-12-30", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2024.12.29.630705", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:59:42.253Z", "modified": "2026-08-20T10:59:42.304Z"}, {"entity": "publication", "iuid": "e799bf76a2334aad9c686bb13e7bc707", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e799bf76a2334aad9c686bb13e7bc707.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e799bf76a2334aad9c686bb13e7bc707"}}, "title": "The impact of Parkinson's disease on striatal network connectivity and corticostriatal drive: An in silico study.", "authors": [{"family": "Carannante", "given": "Ilaria", "initials": "I", "orcid": "0000-0001-8210-8709", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d94ae668884641ec9ba2713e0db64d61.json"}}, {"family": "Scolamiero", "given": "Martina", "initials": "M"}, {"family": "Hjorth", "given": "J J Johannes", "initials": "JJJ", "orcid": "0000-0002-9302-0750", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ec9300bb976d4038a766d908fcd0ce86.json"}}, {"family": "Kozlov", "given": "Alexander", "initials": "A"}, {"family": "Bekkouche", "given": "Bo", "initials": "B"}, {"family": "Guo", "given": "Lihao", "initials": "L", "orcid": "0000-0002-9982-6229", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d3adb76adf48468092952ae4809796d2.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}, {"family": "Chach\u00f3lski", "given": "Wojciech", "initials": "W", "orcid": "0000-0002-2665-9001", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/59be49fa28984d38ac328e451be56820.json"}}, {"family": "Kotaleski", "given": "Jeanette Hellgren", "initials": "JH", "orcid": "0000-0002-0550-0739", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a920517bd1c142878f03bee05e843b62.json"}}], "type": "journal article", "published": "2024-12-10", "journal": {"title": "Netw Neurosci", "issn": "2472-1751", "volume": "8", "issue": "4", "pages": "1149-1172", "issn-l": null}, "abstract": "Striatum, the input stage of the basal ganglia, is important for sensory-motor integration, initiation and selection of behavior, as well as reward learning. Striatum receives glutamatergic inputs from mainly cortex and thalamus. In rodents, the striatal projection neurons (SPNs), giving rise to the direct and the indirect pathway (dSPNs and iSPNs, respectively), account for 95% of the neurons, and the remaining 5% are GABAergic and cholinergic interneurons. Interneuron axon terminals as well as local dSPN and iSPN axon collaterals form an intricate striatal network. Following chronic dopamine depletion as in Parkinson's disease (PD), both morphological and electrophysiological striatal neuronal features have been shown to be altered in rodent models. Our goal with this in silico study is twofold: (a) to predict and quantify how the intrastriatal network connectivity structure becomes altered as a consequence of the morphological changes reported at the single-neuron level and (b) to investigate how the effective glutamatergic drive to the SPNs would need to be altered to account for the activity level seen in SPNs during PD. In summary, we predict that the richness of the connectivity motifs in the striatal network is significantly decreased during PD while, at the same time, a substantial enhancement of the effective glutamatergic drive to striatum is present.", "doi": "10.1162/netn_a_00394", "pmid": "39735495", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11674317"}, {"db": "pii", "key": "netn_a_00394"}], "notes": [], "created": "2026-08-20T12:16:23.614Z", "modified": "2026-08-20T12:16:23.766Z"}, {"entity": "publication", "iuid": "41770c446caf4ee680281bc60b8a6e4f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/41770c446caf4ee680281bc60b8a6e4f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/41770c446caf4ee680281bc60b8a6e4f"}}, "title": "Structural constraints on the emergence of oscillations in multi-population neural networks.", "authors": [{"family": "Zang", "given": "Jie", "initials": "J", "orcid": "0000-0003-2655-3343", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cda7827b6ab3406cbfc0c38859c0fada.json"}}, {"family": "Liu", "given": "Shenquan", "initials": "S"}, {"family": "Helson", "given": "Pascal", "initials": "P", "orcid": "0000-0002-2877-3705", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0ee66ee661c64a4a89df82afceff2e11.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal article", "published": "2024-03-13", "journal": {"title": "Elife", "issn": "2050-084X", "volume": "12", "issn-l": "2050-084X"}, "abstract": "Oscillations arise in many real-world systems and are associated with both functional and dysfunctional states. Whether a network can oscillate can be estimated if we know the strength of interaction between nodes. But in real-world networks (in particular in biological networks) it is usually not possible to know the exact connection weights. Therefore, it is important to determine the structural properties of a network necessary to generate oscillations. Here, we provide a proof that uses dynamical system theory to prove that an odd number of inhibitory nodes and strong enough connections are necessary to generate oscillations in a single cycle threshold-linear network. We illustrate these analytical results in a biologically plausible network with either firing-rate based or spiking neurons. Our work provides structural properties necessary to generate oscillations in a network. We use this knowledge to reconcile recent experimental findings about oscillations in basal ganglia with classical findings.", "doi": "10.7554/eLife.88777", "pmid": "38477669", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10937037"}, {"db": "pii", "key": "88777"}], "notes": [], "created": "2026-08-20T13:55:23.747Z", "modified": "2026-08-20T13:55:23.866Z"}, {"entity": "publication", "iuid": "58833333f12f43fa8d80edf8ded7a54a", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/58833333f12f43fa8d80edf8ded7a54a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/58833333f12f43fa8d80edf8ded7a54a"}}, "title": "Structural constraints on the emergence of oscillations in multi-population neural networks", "authors": [{"family": "Zang", "given": "Jie", "initials": "J", "orcid": "0000-0003-2655-3343", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cda7827b6ab3406cbfc0c38859c0fada.json"}}, {"family": "Liu", "given": "Shenquan", "initials": "S"}, {"family": "Helson", "given": "Pascal", "initials": "P", "orcid": "0000-0002-2877-3705", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0ee66ee661c64a4a89df82afceff2e11.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal-article", "published": "2024-03-13", "journal": {"issn": "2050-084X", "volume": "12", "title": "Elife", "issn-l": "2050-084X"}, "abstract": null, "doi": "10.7554/elife.88777.3", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:55:25.590Z", "modified": "2026-08-20T13:55:25.672Z"}, {"entity": "publication", "iuid": "0a90616dc1584115a7c0c502d4ed0fc3", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0a90616dc1584115a7c0c502d4ed0fc3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0a90616dc1584115a7c0c502d4ed0fc3"}}, "title": "Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia.", "authors": [{"family": "W\u00e4rnberg", "given": "Emil", "initials": "E", "orcid": "0000-0002-4754-4561", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8af425cc26ac4461b99802d64ead587c.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal article", "published": "2023-08-08", "journal": {"title": "Proc. Natl. Acad. Sci. U.S.A.", "issn": "1091-6490", "volume": "120", "issue": "32", "pages": "e2221994120", "issn-l": "0027-8424"}, "abstract": "It is well established that midbrain dopaminergic neurons support reinforcement learning (RL) in the basal ganglia by transmitting a reward prediction error (RPE) to the striatum. In particular, different computational models and experiments have shown that a striatum-wide RPE signal can support RL over a small discrete set of actions (e.g., no/no-go, choose left/right). However, there is accumulating evidence that the basal ganglia functions not as a selector between predefined actions but rather as a dynamical system with graded, continuous outputs. To reconcile this view with RL, there is a need to explain how dopamine could support learning of continuous outputs, rather than discrete action values. Inspired by the recent observations that besides RPE, the firing rates of midbrain dopaminergic neurons correlate with motor and cognitive variables, we propose a model in which dopamine signal in the striatum carries a vector-valued error feedback signal (a loss gradient) instead of a homogeneous scalar error (a loss). We implement a local, \"three-factor\" corticostriatal plasticity rule involving the presynaptic firing rate, a postsynaptic factor, and the unique dopamine concentration perceived by each striatal neuron. With this learning rule, we show that such a vector-valued feedback signal results in an increased capacity to learn a multidimensional series of real-valued outputs. Crucially, we demonstrate that this plasticity rule does not require precise nigrostriatal synapses but remains compatible with experimental observations of random placement of varicosities and diffuse volume transmission of dopamine.", "doi": "10.1073/pnas.2221994120", "pmid": "37527344", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10410740"}], "notes": [], "created": "2026-08-20T09:31:23.796Z", "modified": "2026-08-20T09:31:23.905Z"}, {"entity": "publication", "iuid": "3e27298733cd43ffbefab235d5833ecd", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3e27298733cd43ffbefab235d5833ecd.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3e27298733cd43ffbefab235d5833ecd"}}, "title": "Are single-peaked tuning curves tuned for speed rather than accuracy?", "authors": [{"family": "Lenninger", "given": "Movitz", "initials": "M", "orcid": "0000-0002-6165-4900", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/87757488f4ca44e3af4211b5de813ece.json"}}, {"family": "Skoglund", "given": "Mikael", "initials": "M"}, {"family": "Herman", "given": "Pawel Andrzej", "initials": "PA", "orcid": "0000-0001-6553-823X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c4cadcc49624beb9893821d46064c2d.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "journal article", "published": "2023-05-16", "journal": {"title": "Elife", "issn": "2050-084X", "volume": "12", "issn-l": "2050-084X"}, "abstract": "According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment, given some biophysical constraints. In early visual areas, stimulus-induced modulations of neural activity (or tunings) are predominantly single-peaked. However, periodic tuning, as exhibited by grid cells, has been linked to a significant increase in decoding performance. Does this imply that the tuning curves in early visual areas are sub-optimal? We argue that the time scale at which neurons encode information is imperative to understand the advantages of single-peaked and periodic tuning curves, respectively. Here, we show that the possibility of catastrophic (large) errors creates a trade-off between decoding time and decoding ability. We investigate how decoding time and stimulus dimensionality affect the optimal shape of tuning curves for removing catastrophic errors. In particular, we focus on the spatial periods of the tuning curves for a class of circular tuning curves. We show an overall trend for minimal decoding time to increase with increasing Fisher information, implying a trade-off between accuracy and speed. This trade-off is reinforced whenever the stimulus dimensionality is high, or there is ongoing activity. Thus, given constraints on processing speed, we present normative arguments for the existence of the single-peaked tuning organization observed in early visual areas.", "doi": "10.7554/eLife.84531", "pmid": "37191292", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10259479"}, {"db": "pii", "key": "84531"}], "notes": [], "created": "2026-08-20T13:54:51.694Z", "modified": "2026-08-20T13:54:51.785Z"}, {"entity": "publication", "iuid": "fcaad31b6ae5465096037ab100533eca", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/fcaad31b6ae5465096037ab100533eca.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/fcaad31b6ae5465096037ab100533eca"}}, "title": "Author response: Are single-peaked tuning curves tuned for speed rather than accuracy?", "authors": [{"family": "Lenninger", "given": "Movitz", "initials": "M", "orcid": "0000-0002-6165-4900", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/87757488f4ca44e3af4211b5de813ece.json"}}, {"family": "Skoglund", "given": "Mikael", "initials": "M"}, {"family": "Herman", "given": "Pawel Andrzej", "initials": "PA", "orcid": "0000-0001-6553-823X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c4cadcc49624beb9893821d46064c2d.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "peer-review", "published": "2023-02-28", "journal": {"issn-l": null}, "abstract": null, "doi": "10.7554/elife.84531.sa2", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:54:53.573Z", "modified": "2026-08-20T13:54:53.632Z"}, {"entity": "publication", "iuid": "fd2dcf41e7b849259a479369ec513c93", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/fd2dcf41e7b849259a479369ec513c93.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/fd2dcf41e7b849259a479369ec513c93"}}, "title": "Cortex-wide topography of 1/f-exponent in Parkinson\u2019s disease", "authors": [{"family": "Helson", "given": "Pascal", "initials": "P", "orcid": "0000-0002-2877-3705", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0ee66ee661c64a4a89df82afceff2e11.json"}}, {"family": "Lundqvist", "given": "Daniel", "initials": "D", "orcid": "0000-0003-1593-2559", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/06fbc4c5ba644ef4b6ebeb1cc39c7f08.json"}}, {"family": "Svenningsson", "given": "Per", "initials": "P", "orcid": "0000-0001-6727-3802", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b01bbacfa24e4b9794734bf1121d1c38.json"}}, {"family": "Vinding", "given": "Mikkel C", "initials": "MC", "orcid": "0000-0002-7954-2886", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ccaff4ee9c23497ba518325c7997701b.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "posted-content", "published": "2023-01-20", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.01.19.524792", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:43:31.079Z", "modified": "2026-08-20T10:43:31.221Z"}, {"entity": "publication", "iuid": "7e2fc30d50d4436bbd6aba43408c90fb", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/7e2fc30d50d4436bbd6aba43408c90fb.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/7e2fc30d50d4436bbd6aba43408c90fb"}}, "title": "Role of interneuron subtypes in controlling trial-by-trial output variability in the neocortex", "authors": [{"family": "Guo", "given": "Lihao", "initials": "L", "orcid": "0000-0002-9982-6229", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d3adb76adf48468092952ae4809796d2.json"}}, {"family": "Kumar", "given": "Arvind", "initials": "A", "orcid": "0000-0002-8044-9195", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf2fe30252074acb8d09f88f6c9b55f3.json"}}], "type": "posted-content", "published": "2022-12-06", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.12.06.519329", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:42:46.741Z", "modified": "2026-08-20T10:42:46.836Z"}]}