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Johnston R, Boulay C, Miller K, Sachs A. Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task. Biomed Phys Eng Express 2024; 10:065029. [PMID: 39260393 DOI: 10.1088/2057-1976/ad795e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 09/11/2024] [Indexed: 09/13/2024]
Abstract
Objective. Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a common choice for such a communication system due to their fine temporal and spatial resolution. The small size of these implants makes the implantation plan critical for the successful exfiltration of information, particularly when targeting representations of task goals that lack robust anatomical correlates.Approach. Working memory processes including encoding, retrieval, and maintenance are observed in many areas of the brain. Using human electrocorticography (ECoG) recordings during a working memory experiment, we provide proof that it is possible to localize cognitive activity associated with the task and to identify key locations involved with executive memory functions.Results.From the analysis, we could propose an optimal iBCI implant location with the desired features. The general approach is not limited to working memory but could also be used to map other goal-encoding factors such as movement intentions, decision-making, and visual-spatial attention.Significance. Deciphering the intended action of a BCI user is a complex challenge that involves the extraction and integration of cognitive factors such as movement planning, working memory, visual-spatial attention, and the decision state. Examining field potentials from ECoG electrodes while participants engaged in tailored cognitive tasks can pinpoint location with valuable information related to anticipated actions. This manuscript demonstrates the feasibility of identifying electrodes involved in cognitive activity related to working memory during user engagement in the NBack task. Devoting time in meticulous preparation to identify the optimal brain regions for BCI implant locations will increase the likelihood of rich signal outcomes, thereby improving the overall BCI user experience.
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Affiliation(s)
- Renée Johnston
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, Canada
| | - Chadwick Boulay
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, Canada
| | - Kai Miller
- Department of Neurologic Surgery, Mayo Clinic, 200 First St. Rochester, MN, 55902, United States of America
| | - Adam Sachs
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, Canada
- Division of Neurosurgery, Ottawa Hospital Research Institute, Ottawa, ON, Canada
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Ouchi T, Scholl LR, Rajeswaran P, Canfield RA, Smith LI, Orsborn AL. Mapping eye, arm, and reward information in frontal motor cortices using electrocorticography in non-human primates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.13.607846. [PMID: 39185198 PMCID: PMC11343120 DOI: 10.1101/2024.08.13.607846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Goal-directed reaches give rise to dynamic neural activity across the brain as we move our eyes and arms, and process outcomes. High spatiotemporal resolution mapping of multiple cortical areas will improve our understanding of how these neural computations are spatially and temporally distributed across the brain. In this study, we used micro-electrocorticography (μECoG) recordings in two male monkeys performing visually guided reaches to map information related to eye movements, arm movements, and receiving rewards over a 1.37 cm2 area of frontal motor cortices (primary motor cortex, premotor cortex, frontal eye field, and dorsolateral pre-frontal cortex). Time-frequency and decoding analyses revealed that eye and arm movement information shifts across brain regions during a reach, likely reflecting shifts from planning to execution. We then used phase-based analyses to reveal potential overlaps of eye and arm information. We found that arm movement decoding performance was impacted by task-irrelevant eye movements, consistent with the presence of intermixed eye and arm information across much of motor cortices. Phase-based analyses also identified reward-related activity primarily around the principal sulcus in the pre-frontal cortex as well as near the arcuate sulcus in the premotor cortex. Our results demonstrate μECoG's strengths for functional mapping and provide further detail on the spatial distribution of eye, arm, and reward information processing distributed across frontal cortices during reaching. These insights advance our understanding of the overlapping neural computations underlying coordinated movements and reveal opportunities to leverage these signals to enhance future brain-computer interfaces.
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Affiliation(s)
- Tomohiro Ouchi
- University of Washington, Electrical and Computer Engineering, Seattle, 98115, USA
| | - Leo R Scholl
- University of Washington, Electrical and Computer Engineering, Seattle, 98115, USA
| | | | - Ryan A Canfield
- University of Washington, Bioengineering, Seattle, 98115, USA
| | - Lydia I Smith
- University of Washington, Electrical and Computer Engineering, Seattle, 98115, USA
| | - Amy L Orsborn
- University of Washington, Electrical and Computer Engineering, Seattle, 98115, USA
- University of Washington, Bioengineering, Seattle, 98115, USA
- Washington National Primate Research Center, Seattle, Washington, 98115, USA
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Rouzitalab A, Boulay CB, Park J, Martinez-Trujillo JC, Sachs AJ. Ensembles code for associative learning in the primate lateral prefrontal cortex. Cell Rep 2023; 42:112449. [PMID: 37119136 DOI: 10.1016/j.celrep.2023.112449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 02/01/2023] [Accepted: 04/13/2023] [Indexed: 04/30/2023] Open
Abstract
The lateral prefrontal cortex (LPFC) of primates is thought to play a role in associative learning. However, it remains unclear how LPFC neuronal ensembles dynamically encode and store memories for arbitrary stimulus-response associations. We recorded the activity of neurons in LPFC of two macaques during an associative learning task using multielectrode arrays. During task trials, the color of a symbolic cue indicated the location of one of two possible targets for a saccade. During a trial block, multiple randomly chosen associations were learned by the subjects. A state-space analysis indicated that LPFC neuronal ensembles rapidly learn new stimulus-response associations mirroring the animals' learning. Multiple associations acquired during training are stored in a neuronal subspace and can be retrieved hours after learning. Finally, knowledge of old associations facilitates learning new, similar associations. These results indicate that neuronal ensembles in the primate LPFC provide a flexible and dynamic substrate for associative learning.
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Affiliation(s)
- Alireza Rouzitalab
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 9A7, Canada; The Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada.
| | - Chadwick B Boulay
- The Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada; Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Jeongwon Park
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 9A7, Canada; Department of Electrical and Biomedical Engineering, University of Nevada, Reno, NV 89557, USA
| | - Julio C Martinez-Trujillo
- Department of Physiology and Pharmacology and Psychiatry, and Western Institute for Neuroscience, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON N6A 5K8, Canada.
| | - Adam J Sachs
- The Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada; Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada.
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Johnston R, Abbass M, Corrigan B, Gulli R, Martinez-Trujillo J, Sachs A. Decoding spatial locations from primate lateral prefrontal cortex neural activity during virtual navigation. J Neural Eng 2023; 20. [PMID: 36693278 DOI: 10.1088/1741-2552/acb5c2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 01/24/2023] [Indexed: 01/25/2023]
Abstract
Objective. Decoding the intended trajectories from brain signals using a brain-computer interface system could be used to improve the mobility of patients with disabilities.Approach. Neuronal activity associated with spatial locations was examined while macaques performed a navigation task within a virtual environment.Main results.Here, we provide proof of principle that multi-unit spiking activity recorded from the lateral prefrontal cortex (LPFC) of non-human primates can be used to predict the location of a subject in a virtual maze during a navigation task. The spatial positions within the maze that require a choice or are associated with relevant task events can be better predicted than the locations where no relevant events occur. Importantly, within a task epoch of a single trial, multiple locations along the maze can be independently identified using a support vector machine model.Significance. Considering that the LPFC of macaques and humans share similar properties, our results suggest that this area could be a valuable implant location for an intracortical brain-computer interface system used for spatial navigation in patients with disabilities.
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Affiliation(s)
- Renée Johnston
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Mohamad Abbass
- Department of Clinical Neurological Sciences, London Health Sciences Centre, Western University, London, ON, Canada.,Western Institute for Neuroscience, Western University, London, ON, Canada.,Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Benjamin Corrigan
- Western Institute for Neuroscience, Western University, London, ON, Canada.,Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Roberto Gulli
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States of America.,Center for Theoretical Neuroscience, Columbia University, New York, NY, United States of America
| | - Julio Martinez-Trujillo
- Western Institute for Neuroscience, Western University, London, ON, Canada.,Department of Physiology, Pharmacology, and Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Adam Sachs
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada.,Division of Neurosurgery, Ottawa Hospital Research Institute, Ottawa, ON, Canada
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5
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Roussy M, Corrigan B, Luna R, Gulli RA, Sachs AJ, Palaniyappan L, Martinez-Trujillo JC. Stable Working Memory and Perceptual Representations in Macaque Lateral Prefrontal Cortex during Naturalistic Vision. J Neurosci 2022; 42:8328-8342. [PMID: 36195438 PMCID: PMC9653275 DOI: 10.1523/jneurosci.0597-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/19/2022] [Accepted: 08/03/2022] [Indexed: 11/21/2022] Open
Abstract
Primates use perceptual and mnemonic visuospatial representations to perform everyday functions. Neurons in the lateral prefrontal cortex (LPFC) have been shown to encode both of these representations during tasks where eye movements are strictly controlled and visual stimuli are reduced in complexity. This raises the question of whether perceptual and mnemonic representations encoded by LPFC neurons remain robust during naturalistic vision-in the presence of a rich visual scenery and during eye movements. Here we investigate this issue by training macaque monkeys to perform working memory and perception tasks in a visually complex virtual environment that requires navigation using a joystick and allows for free visual exploration of the scene. We recorded the activity of 3950 neurons in the LPFC (areas 8a and 9/46) of two male rhesus macaques using multielectrode arrays, and measured eye movements using video tracking. We found that navigation trajectories to target locations and eye movement behavior differed between the perception and working memory tasks, suggesting that animals used different behavioral strategies. Single neurons were tuned to target location during cue encoding and working memory delay, and neural ensemble activity was predictive of the behavior of the animals. Neural decoding of the target location was stable throughout the working memory delay epoch. However, neural representations of similar target locations differed between the working memory and perception tasks. These findings indicate that during naturalistic vision, LPFC neurons maintain robust and distinct neural codes for mnemonic and perceptual visuospatial representations.SIGNIFICANCE STATEMENT We show that lateral prefrontal cortex neurons encode working memory and perceptual representations during a naturalistic task set in a virtual environment. We show that despite eye movement and complex visual input, neurons maintain robust working memory representations of space, which are distinct from neuronal representations for perception. We further provide novel insight into the use of virtual environments to construct behavioral tasks for electrophysiological experiments.
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Affiliation(s)
- Megan Roussy
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5C1, Canada
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Benjamin Corrigan
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5C1, Canada
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
| | - Rogelio Luna
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5C1, Canada
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
| | - Roberto A Gulli
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027
| | - Adam J Sachs
- The Ottawa Hospital, University of Ottawa, Ottawa, Ontario K1H 8L6, Canada
| | - Lena Palaniyappan
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Centre for Youth Mental Health, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Julio C Martinez-Trujillo
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5C1, Canada
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
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Heusser MR, Bourrelly C, Gandhi NJ. Decoding the Time Course of Spatial Information from Spiking and Local Field Potential Activities in the Superior Colliculus. eNeuro 2022; 9:ENEURO.0347-22.2022. [PMID: 36379711 PMCID: PMC9718355 DOI: 10.1523/eneuro.0347-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 10/31/2022] [Accepted: 11/05/2022] [Indexed: 11/17/2022] Open
Abstract
Place code representation is ubiquitous in circuits that encode spatial parameters. For visually guided eye movements, neurons in many brain regions emit spikes when a stimulus is presented in their receptive fields and/or when a movement is directed into their movement fields. Crucially, individual neurons respond for a broad range of directions or eccentricities away from the optimal vector, making it difficult to decode the stimulus location or the saccade vector from each cell's activity. We investigated whether it is possible to decode the spatial parameter with a population-level analysis, even when the optimal vectors are similar across neurons. Spiking activity and local field potentials (LFPs) in the superior colliculus (SC) were recorded with a laminar probe as monkeys performed a delayed saccade task to one of eight targets radially equidistant in direction. A classifier was applied offline to decode the spatial configuration as the trial progresses from sensation to action. For spiking activity, decoding performance across all eight directions was highest during the visual and motor epochs and lower but well above chance during the delay period. Classification performance followed a similar pattern for LFP activity too, except the performance during the delay period was limited mostly to the preferred direction. Increasing the number of neurons in the population consistently increased classifier performance for both modalities. Overall, this study demonstrates the power of population activity for decoding spatial information not possible from individual neurons.
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Affiliation(s)
- Michelle R Heusser
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213
- Center for Neural Basis of Cognition (CNBC), University of Pittsburgh, Pittsburgh, PA 15213
| | - Clara Bourrelly
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213
- Center for Neural Basis of Cognition (CNBC), University of Pittsburgh, Pittsburgh, PA 15213
| | - Neeraj J Gandhi
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213
- Center for Neural Basis of Cognition (CNBC), University of Pittsburgh, Pittsburgh, PA 15213
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15213
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Howland JG, Ito R, Lapish CC, Villaruel FR. The rodent medial prefrontal cortex and associated circuits in orchestrating adaptive behavior under variable demands. Neurosci Biobehav Rev 2022; 135:104569. [PMID: 35131398 PMCID: PMC9248379 DOI: 10.1016/j.neubiorev.2022.104569] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 12/17/2021] [Accepted: 02/01/2022] [Indexed: 11/28/2022]
Abstract
Emerging evidence implicates rodent medial prefrontal cortex (mPFC) in tasks requiring adaptation of behavior to changing information from external and internal sources. However, the computations within mPFC and subsequent outputs that determine behavior are incompletely understood. We review the involvement of mPFC subregions, and their projections to the striatum and amygdala in two broad types of tasks in rodents: 1) appetitive and aversive Pavlovian and operant conditioning tasks that engage mPFC-striatum and mPFC-amygdala circuits, and 2) foraging-based tasks that require decision making to optimize reward. We find support for region-specific function of the mPFC, with dorsal mPFC and its projections to the dorsomedial striatum supporting action control with higher cognitive demands, and ventral mPFC engagement in translating affective signals into behavior via discrete projections to the ventral striatum and amygdala. However, we also propose that defined mPFC subdivisions operate as a functional continuum rather than segregated functional units, with crosstalk that allows distinct subregion-specific inputs (e.g., internal, affective) to influence adaptive behavior supported by other subregions.
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Affiliation(s)
- John G Howland
- Department of Anatomy, Physiology, and Pharmacology, University of Saskatchewan, Saskatoon, SK, Canada.
| | - Rutsuko Ito
- Department of Psychology, University of Toronto-Scarborough, Toronto, ON, Canada.
| | - Christopher C Lapish
- Department of Psychology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA.
| | - Franz R Villaruel
- Department of Psychology, Concordia University, Montreal, QC, Canada.
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8
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Johnston R, Doucet G, Boulay C, Miller K, Martinez-Trujillo J, Sachs A. Decoding Saccade Intention From Primate Prefrontal Cortical Local Field Potentials Using Spectral, Spatial, and Temporal Dimensionality Reduction. Int J Neural Syst 2021; 31:2150023. [PMID: 33931006 DOI: 10.1142/s0129065721500234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Most invasive Brain Computer Interfaces (iBCIs) use spike and Local Field Potentials (LFPs) from the motor or parietal cortices to decode movement intentions. It has been debated whether harvesting signals from other brain areas that encode global cognitive variables, such as the allocation of attention and eye movement goals in a variety of spatial reference frames, may improve the outcome of iBCIs. Here, we explore the ability of LFP signals, sampled from the lateral prefrontal cortex (LPFC) of macaque monkeys, to encode eye-movement intention during the pre-movement fixation period of a delayed saccade task. We use spectral dimensionality reduction to examine the spatiotemporal properties of the extracted non-rhythmic broadband activity and explore its usefulness in decoding saccade goals. The dynamics of the broadband signal in low spatial dimensions across the pre-movement fixation period uncovered saccade target separation; its discriminative potential was confirmed using support vector machine classifications. These findings reveal that broadband LFP from the LPFC can be used to decode intended saccade target location during pre-movement periods. We further provide a general workflow that can be implemented in iBCIs and it is relatively robust to the loss of spikes in individual electrodes.
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Affiliation(s)
- Renée Johnston
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, K1Y 4E9, Canada
| | - Guillaume Doucet
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, K1Y 4E9, Canada
| | - Chadwick Boulay
- Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, K1Y 4E9, Canada
| | - Kai Miller
- Department of Neurologic Surgery, Mayo Clinic, 200 First St., Rochester, MN 55902, United States
| | - Julio Martinez-Trujillo
- Robarts Research Institute, Western University, 1151 Richmond Street N., London, ON, N6A 5B7, Canada
| | - Adam Sachs
- Division of Neurosurgery, Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, K1Y 4E9, Canada
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Issar D, Williamson RC, Khanna SB, Smith MA. A neural network for online spike classification that improves decoding accuracy. J Neurophysiol 2020; 123:1472-1485. [PMID: 32101491 PMCID: PMC7191521 DOI: 10.1152/jn.00641.2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 02/26/2020] [Accepted: 02/26/2020] [Indexed: 11/22/2022] Open
Abstract
Separating neural signals from noise can improve brain-computer interface performance and stability. However, most algorithms for separating neural action potentials from noise are not suitable for use in real time and have shown mixed effects on decoding performance. With the goal of removing noise that impedes online decoding, we sought to automate the intuition of human spike-sorters to operate in real time with an easily tunable parameter governing the stringency with which spike waveforms are classified. We trained an artificial neural network with one hidden layer on neural waveforms that were hand-labeled as either spikes or noise. The network output was a likelihood metric for each waveform it classified, and we tuned the network's stringency by varying the minimum likelihood value for a waveform to be considered a spike. Using the network's labels to exclude noise waveforms, we decoded remembered target location during a memory-guided saccade task from electrode arrays implanted in prefrontal cortex of rhesus macaque monkeys. The network classified waveforms in real time, and its classifications were qualitatively similar to those of a human spike-sorter. Compared with decoding with threshold crossings, in most sessions we improved decoding performance by removing waveforms with low spike likelihood values. Furthermore, decoding with our network's classifications became more beneficial as time since array implantation increased. Our classifier serves as a feasible preprocessing step, with little risk of harm, that could be applied to both off-line neural data analyses and online decoding.NEW & NOTEWORTHY Although there are many spike-sorting methods that isolate well-defined single units, these methods typically involve human intervention and have inconsistent effects on decoding. We used human classified neural waveforms as training data to create an artificial neural network that could be tuned to separate spikes from noise that impaired decoding. We found that this network operated in real time and was suitable for both off-line data processing and online decoding.
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Affiliation(s)
- Deepa Issar
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
- University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ryan C Williamson
- University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Machine Learning, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Carnegie Mellon Neuroscience Institute, Pittsburgh, Pennsylvania
| | - Sanjeev B Khanna
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Matthew A Smith
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Carnegie Mellon Neuroscience Institute, Pittsburgh, Pennsylvania
- Department of Ophthalmology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
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Encoding of the Intent to Drink Alcohol by the Prefrontal Cortex Is Blunted in Rats with a Family History of Excessive Drinking. eNeuro 2019; 6:ENEURO.0489-18.2019. [PMID: 31358511 PMCID: PMC6712204 DOI: 10.1523/eneuro.0489-18.2019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 04/19/2019] [Accepted: 06/01/2019] [Indexed: 11/21/2022] Open
Abstract
The prefrontal cortex (PFC) plays a central role in guiding decision making, and its function is altered by alcohol use and an individual's innate risk for excessive alcohol drinking. The primary goal of this work was to determine how neural activity in the PFC guides the decision to drink. Towards this goal, the within-session changes in neural activity were measured from medial PFC (mPFC) of rats performing a drinking procedure that allowed them to consume or abstain from alcohol in a self-paced manner. Recordings were obtained from rats that either lacked or expressed an innate risk for excessive alcohol intake, Wistar or alcohol-preferring (P) rats, respectively. Wistar rats exhibited patterns of neural activity consistent with the intention to drink or abstain from drinking, whereas these patterns were blunted or absent in P rats. Collectively, these data indicate that neural activity patterns in mPFC associated with the intention to drink alcohol are influenced by innate risk for excessive alcohol drinking. This observation may indicate a lack of control over the decision to drink by this otherwise well-validated supervisory brain region.
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Duong L, Leavitt M, Pieper F, Sachs A, Martinez-Trujillo J. A Normalization Circuit Underlying Coding of Spatial Attention in Primate Lateral Prefrontal Cortex. eNeuro 2019; 6:ENEURO.0301-18.2019. [PMID: 31001577 PMCID: PMC6469883 DOI: 10.1523/eneuro.0301-18.2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 02/14/2019] [Accepted: 02/25/2019] [Indexed: 11/26/2022] Open
Abstract
Lateral prefrontal cortex (LPFC) neurons signal the allocation of voluntary attention; however, the neural computations underlying this function remain unknown. To investigate this, we recorded from neuronal ensembles in the LPFC of two Macaca fascicularis performing a visuospatial attention task. LPFC neural responses to a single stimulus were normalized when additional stimuli/distracters appeared across the visual field and were well-characterized by an averaging computation. Deploying attention toward an individual stimulus surrounded by distracters shifted neural activity from an averaging regime toward a regime similar to that when the attended stimulus was presented in isolation (winner-take-all; WTA). However, attentional modulation is both qualitatively and quantitatively dependent on a neuron's visuospatial tuning. Our results show that during attentive vision, LPFC neuronal ensemble activity can be robustly read out by downstream areas to generate motor commands, and/or fed back into sensory areas to filter out distracter signals in favor of target signals.
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Affiliation(s)
- Lyndon Duong
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
- Robarts Research Institute, London, Ontario N6A 5B7, Canada
| | - Matthew Leavitt
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
- Robarts Research Institute, London, Ontario N6A 5B7, Canada
- Department of Physiology, McGill University, Quebec H3A 0G4, Canada Montreal
| | - Florian Pieper
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg 52 20246, Germany
| | - Adam Sachs
- The Ottawa Hospital, University of Ottawa, Ottawa, Ontario K1H 8L6, Canada
| | - Julio Martinez-Trujillo
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
- Robarts Research Institute, London, Ontario N6A 5B7, Canada
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Jia N, Brincat SL, Salazar-Gómez AF, Panko M, Guenther FH, Miller EK. Decoding of intended saccade direction in an oculomotor brain-computer interface. J Neural Eng 2018; 14:046007. [PMID: 28098561 DOI: 10.1088/1741-2552/aa5a3e] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
OBJECTIVE To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from the hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. APPROACH We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. MAIN RESULTS Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. SIGNIFICANCE Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for 'point and click' computer operation as used in most current AAC systems.
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Affiliation(s)
- Nan Jia
- Center for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America. Graduate Program in Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America
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13
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Ebbesen D, Olsen J. Motor Intention/Intentionality and Associationism - A conceptual review. Integr Psychol Behav Sci 2018; 52:565-594. [PMID: 29882127 DOI: 10.1007/s12124-018-9441-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Motor intention/intentionality (MI) has been investigated from many different angles. Some researchers focus on the purely physical and mechanical aspects of the human motor system, while others emphasize the subjectivity involved in intentionality. While bridging this seemingly dualistic gap between the two concepts ought to be the researcher's' main task, different schools of thought have instead specialized in stressing one (objective) or the other (subjective) part of this construct. Thus, we find everything from neuroscientific to phenomenologically inspired approaches to MI. The purpose of this article is to review the literature regarding these different approaches to the MI construct. In reviewing the literature, we introduce a broadened conception of associationism. In organizing our data in relation to the laws of association, a lack of methodology clearly manifests itself. Hence, 123 articles out of 143 meet the criteria of our definition of associationism. It seems that this old doctrine sneaks in to a big part of the research rather implicitly through a lack of methodology. To shed light on how this happens in the 123 articles, we develop a continuum to show to which extend associationism operates on a transcendent or substantial level in each article. We find only very few articles that seem to try to gap the bridge between motor and intention/intentionality, and thus we suggest that future MI research reintroduce methodological debates concerning the conceptual character of this construct.
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Affiliation(s)
- Denis Ebbesen
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
| | - Jeppe Olsen
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
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14
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Electrical stimulation of macaque lateral prefrontal cortex modulates oculomotor behavior indicative of a disruption of top-down attention. Sci Rep 2017; 7:17715. [PMID: 29255155 PMCID: PMC5735183 DOI: 10.1038/s41598-017-18153-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 12/07/2017] [Indexed: 11/27/2022] Open
Abstract
The lateral prefrontal cortex (lPFC) of primates is hypothesized to be heavily involved in decision-making and selective visual attention. Recent neurophysiological evidence suggests that information necessary for an orchestration of those high-level cognitive factors are indeed represented in the lPFC. However, we know little about the specific contribution of sub-networks within lPFC to the deployment of top-down influences that can be measured in extrastriate visual cortex. Here, we systematically applied electrical stimulations to areas 8Av and 45 of two macaque monkeys performing a concurrent goal-directed saccade task. Despite using currents well above saccadic thresholds of the directly adjacent Frontal Eye Fields (FEF), saccades were only rarely evoked by the stimulation. Instead, two types of behavioral effects were observed: Stimulations of caudal sites in 8Av (close to FEF) shortened or prolonged saccadic reaction times, depending on the task-instructed saccade, while rostral stimulations of 8Av/45 seem to affect the relative attentional weighting of saccade targets as well as saccadic reaction times. These results illuminate important differences in the causal involvement of different sub-networks within the lPFC and are most compatible with a stimulation-induced biasing of stimulus processing that accelerates the detection of saccade targets presented ipsilateral to stimulation through a disruption of contralaterally deployed top-down attention.
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Leavitt ML, Pieper F, Sachs AJ, Martinez-Trujillo JC. A Quadrantic Bias in Prefrontal Representation of Visual-Mnemonic Space. Cereb Cortex 2017; 28:2405-2421. [DOI: 10.1093/cercor/bhx142] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Indexed: 11/13/2022] Open
Affiliation(s)
- Matthew L Leavitt
- Department of Physiology, McGill University, Montreal, Quebec, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, Ontario, Canada
| | - Florian Pieper
- Department of Neuro- & Pathophysiology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Adam J Sachs
- Division of Neurosurgery, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Julio C Martinez-Trujillo
- Department of Physiology, McGill University, Montreal, Quebec, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, Ontario, Canada
- Robarts Research Institute, University of Western Ontario, Ontario, Canada
- Brain and Mind Institute, University of Western Ontario, Ontario, Canada
- Department of Psychiatry, University of Western Ontario, Ontario, Canada
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16
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Rich EL, Wallis JD. Decoding subjective decisions from orbitofrontal cortex. Nat Neurosci 2016; 19:973-80. [PMID: 27273768 PMCID: PMC4925198 DOI: 10.1038/nn.4320] [Citation(s) in RCA: 202] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 05/05/2016] [Indexed: 12/02/2022]
Abstract
When making a subjective choice, the brain must compute a value for each option and compare those values to make a decision. The orbitofrontal cortex (OFC) is critically involved in this process, but the neural mechanisms remain obscure, in part due to limitations in our ability to measure and control the internal deliberations that can alter the dynamics of the decision process. Here, we tracked the dynamics by recovering temporally precise neural states from multi-dimensional data in OFC. During individual choices, OFC alternated between states associated with the value of two available options, with dynamics that predicted whether a subject would decide quickly or vacillate between the two alternatives. Ensembles of value-encoding neurons contributed to these states, with individual neurons shifting activity patterns as the network evaluated each option. Thus, the mechanism of subjective decision-making involves the dynamic activation of OFC states associated with each choice alternative.
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Affiliation(s)
- Erin L Rich
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, USA
| | - Jonathan D Wallis
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, USA.,Department of Psychology, University of California at Berkeley, Berkeley, California, USA
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