Spike-field activity in parietal area LIP during coordinated reach and saccade movements

Hagan, Maureen A.; Dean, Heather L.; Pesaran, Bijan

doi:10.1152/jn.00867.2011

Cited by 50 publications

(52 citation statements)

References 119 publications

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“…The LFP is becoming a common measurement of neuronal population activity in multiple cortical areas including V1 ( Victor et al 1994 ; Kayser and Konig 2004 ; Jia et al 2011 ; Lashgari et al 2012 ), V4 ( Sundberg et al 2012 ; Mineault et al 2013 ), MT ( Liu and Newsome 2006 ; Khayat et al 2010 ), and IT ( Pesaran et al 2002 ; Banerjee et al 2010 ; Hagan et al 2012 ). Although recordings from spikes measure directly the neuronal output, single neuronal recordings usually last a few hours and only rarely extend for much longer ( Swadlow 1985 ).…”

Section: Discussionmentioning

confidence: 99%

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

Jansen¹,

Li²,

Lashgari

et al. 2014

Cereb. Cortex

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Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color.

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Section: Discussionmentioning

confidence: 99%

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

Jansen¹,

Li²,

Lashgari

et al. 2014

Cereb. Cortex

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“…Several cortical regions exhibit very strong oscillations under specific sensory or behavioral conditions. For example: there is a strong source of gamma in V1/V2 (Gray et al, 1989;Peter et al, 2019;Vinck and Bosman, 2016;Onorato et al, 2020;Henrie and Shapley, 2005;Spyropoulos et al, 2020); beta in parieto-frontal cortex (Figure 1, (Scherberger et al, 2005;Dann et al, 2016;Brovelli et al, 2004;Salazar et al, 2012b;Hagan et al, 2012;Donoghue et al, 1998;Murthy and Fetz, 1996)); and theta and gamma in rodent hippocampus (Buzsáki, 2006;Colgin et al, 2009;Bragin et al, 1995). Coherence between these oscillatory sources and areas with weak or no intrinsic oscillations will be dominated by synaptic mixing (Figure 1, (Schomburg et al, 2014)).…”

Section: Selective Communication Is Implemented Through Selec-mentioning

confidence: 99%

A general theory of coherence between brain areas

Schneider

Dann

Sheshadri

et al. 2020

Preprint

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What does neuronal coherence tell us about neuronal communication? Does coherence between field potentials (e.g. LFP, EEG, MEG) reflect spiking entrainment or coupling between oscillators? Is it a mechanism for communication between brain areas, or a byproduct of interareal connectivity? We hypothesized that interareal coherence is explained by the fact that outputs from one cortical area give rise to synaptic inputs in the same brain area, and correlated synaptic inputs in another area. Our mathematical analysis demonstrates that coherence between a sending and receiving area is precisely predicted from only two parameters: Interareal connectivity and oscillatory synchronization in the sending area. This model predicts narrow-band coherence even in case of a flat transfer function and in the absence of spiking entrainment in a downstream area, and reproduces frequency-specific Granger-causality patterns between brain areas (gamma feedforward, beta feedback). In general, we find that Granger-causality between field potentials is dominated by oscillatory synchronization in the sending area, whereas spiking entrainment is determined by the resonant properties of the receiver. Our model accurately reproduces LFP-LFP beta-coherence between macaque areas 7B and F5 in the absence of beta phase-locking within area F5. Together, these findings uncover a precise mechanistic model of interareal coherence as a (by)product of connectivity and power.

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“…Firing rates of neurons in the PPC encode movement intention and the temporal evolution of movement choices (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) as well as decision variables such as expected rewards, the subjective desirability during reward-guided decisions (14)(15)(16)(17)(18), and the certainty in perceptual decisions (19). Decisions are made within a network that extends across many regions of the brain (20)(21)(22)(23)(24)(25), so efficient and flexible mechanisms are required to enable distributed computations.…”

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confidence: 99%

Temporal coding of reward-guided choice in the posterior parietal cortex

Hawellek

Wong

Pesaran

2016

Proc. Natl. Acad. Sci. U.S.A.

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Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks.decision making | phase-of-firing | neural code | saccade | reach T he posterior parietal cortex (PPC) integrates sensory signals for impending actions. Firing rates of neurons in the PPC encode movement intention and the temporal evolution of movement choices (1-13) as well as decision variables such as expected rewards, the subjective desirability during reward-guided decisions (14-18), and the certainty in perceptual decisions (19). Decisions are made within a network that extends across many regions of the brain (20-25), so efficient and flexible mechanisms are required to enable distributed computations. Dynamic and frequency-specific correlations in activity between brain areas are ubiquitous and offer potential physiological mechanisms supporting distributed computations in decision networks (13,21,(26)(27)(28)(29)(30)(31)(32)(33)(34). We hypothesize that the encoding of decisions in the PPC should depend on the temporal structure present in neuronal activity. Previous studies have shown that coherently active ensembles of cells in the PPC predict reaction times (9) and movement choices (13, 21) better than neurons without coherent dynamics. However, whether and how the coding of decisions depends on the temporally structured firing of PPC neurons remains unknown. We examined temporal structure in the encoding of look-reach decisions by PPC neurons. ResultsWe analyzed the activity of 149 units [97 units (31 single units and 66 multiun...

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Spike-field activity in parietal area LIP during coordinated reach and saccade movements

Cited by 50 publications

References 119 publications

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

A general theory of coherence between brain areas

Temporal coding of reward-guided choice in the posterior parietal cortex

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