Phase Locking of Single Neuron Activity to Theta Oscillations during Working Memory in Monkey Extrastriate Visual Cortex

Lee, Han; Simpson, Gregory V.; Logothetis, Nikos K.; Rainer, Gregor

doi:10.1016/j.neuron.2004.12.025

Cited by 364 publications

(319 citation statements)

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“…They reflect the area's input activity in terms of population excitatory and inhibitory postsynaptic potentials, but also the area's regional processing because they are directly affected by dendritic spikes, voltagegated oscillations, and various after-potentials-all markers of diverse neural computations (see Buszáki 2006 for an overview). Not surprisingly, an increasing number of studies report their specificity and usefulness in the search for neural correlates of behavior (Kreiman et al 2006;Lee et al 2005;Liu and Newsome 2006;Osipova et al 2006;Rubino et al 2006;Scherberger et al 2005). Although these studies show that LFPs convey information that is to some degree independent of spiking activity, it has been suggested and demonstrated by many researchers that spikes synchronize to-or that synchronization gives rise to-specific oscillation frequency of the LFPs, in particular ␥-bands (Ͼ40 Hz) in visual cortex and -band (4 -8 Hz) in the hippocampus (see Buszáki 2006 and references therein).…”

Section: Discussionmentioning

confidence: 99%

Inferring Spike Trains From Local Field Potentials

Rasch¹,

Gretton²,

Murayama³

et al. 2008

Journal of Neurophysiology

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We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100-ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high ␥-range (40 -90 Hz) and information contained in lowfrequency oscillations (Ͻ10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during seminatural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of non-anesthetized monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g., LFPs derived from recordings in the dorsal lateral geniculate nucleus) hold no useful information for predicting spiking activity.

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Section: Discussionmentioning

confidence: 99%

Inferring Spike Trains From Local Field Potentials

Rasch¹,

Gretton²,

Murayama³

et al. 2008

Journal of Neurophysiology

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206

200

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“…Several studies have described correlations between Theta activity and WM performance (Givens and Olton 1995;Sauseng et al 2004;Jensen and Lisman 2005;Lee et al 2005). The reduction or block of Theta rhythm interferes with the performance in various WM tasks (Winson 1978;Givens andOlton 1990, 1995), and the amplitude of Theta correlated with the ability to perform well in WM tasks (Klimesch et al 2001;Seager et al 2002;Griffin et al 2004).…”

Section: How Can Increased Theta Affect Wm?mentioning

confidence: 99%

“…Theta activity is an indicator of attention processes and cognitive activity across species and is observed in particular during the performance of complex tasks that require WM. Several studies have described correlations between Theta activity and WM performance in humans, primates, and rodents (Givens and Olton 1995;Kahana et al 2001;Jensen et al 2002;Lee et al 2005). Furthermore, the hippocampus of the rat appears to play an important role in WM storage.…”

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confidence: 99%

Lack of the metabotropic glutamate receptor subtype 7 selectively modulates Theta rhythm and working memory

Hölscher

Schmid²,

Pilz³

et al. 2005

Learn. Mem.

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Metabotropic glutamate receptors (mGluRs) are known to play a role in synaptic plasticity and learning. We have previously shown that mGluR7 deletion in mice produces a selective working memory (WM) impairment, while other types of memory such as reference memory remain unaffected. Since WM has been associated with Theta activity (6-12 Hz) in EEGs, and since EEG abnormalities have been observed in these mice before, we studied the effect of mGluR7 gene ablation on EEG activity in the hippocampus, in particular in the Theta range, during performance of a WM task. In an eight-arm maze with four arms baited, mGluR7 knock-out (KO) and wild-type mice committed the same number of reference memory errors, whereas KOs committed more WM errors. While performing the task, KO mice showed substantially higher Theta amplitudes, and the ratio of Theta to overall EEG power was much increased. No change was seen in the Delta (0-5 Hz), or Gamma (30-40 Hz) EEG bands compared with controls. When recording EEGs during periods of rest in the home cages, no difference was seen between groups. These findings suggest that mGluR7 is important for modulation and control of Theta activity. Since only WM was affected, and only the Theta range of EEG activity was altered, these results show a correlation between Theta rhythm and WM performance, and therefore support the concept that Theta activity in the hippocampus is involved in WM storage.Metabotropic glutamate receptors (mGluRs) are a family of glutamate-sensitive receptors that are coupled to intracellular signal transduction via G-proteins (Pin and Duvoisin 1995). It is known that mGluRs play an important role in the regulation of CNS synaptic plasticity, and also in some processes of memory formation. Pharmacological blockade of mGluR group III receptors (subtypes 4, 6, 7, and 8) has profound effects on the induction of synaptic plasticity (Bashir et al. 1993;Richter-Levin et al. 1994;Hölscher et al. 1997a), synaptic depression (Manahan-Vaughan 2000;Weber et al. 2002), and spatial learning (Hölscher et al. 1996(Hölscher et al. , 1999.In a previous study, we tested the effect of mGluR7 deletion on different forms of learning and memory formation (Hölscher 2003). We showed that mGluR7-deficient (knock-out; KO) mice were not impaired in a non-associative habituation task or in performing reference memory tasks of different complexities (open field, T-maze, four-and eight-arm mazes). However, in tasks that require increased capacity of working memory (WM) performance, mGluR7 KO mice showed clear deficits.WM contains task-related information required to develop plans of action and to guide behavior (Baddeley and Hitch 1974;Olton et al. 1979). In the present paper, we adhere to the definition of WM by Olton et al. (1979), who emphasized the importance of hippocampal activity for supporting WM. How WM is actually encoded and stored in the brain has been under investigation for a long time. The occurrence of oscillations in the EEG of subjects that performed WM tasks had been observed. In pa...

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“…This hypothesis is motivated by theoretical models of cognitive control, such as guided activation theory, in which internal goals specify mappings of weights between posterior brain regions to route information through goal-relevant pathways (12,13). Moreover, this hypothesis is prompted by neurophysiological findings from nonhuman primates (14) that attention coordinates neural activity between extrastriate and frontoparietal cortex by coupling neuronal spikes with local field potentials (LFPs) (15,16) and increasing long-range LFP coherence (17,18). Here we exploit the spatial coverage and noninvasiveness of fMRI to assess how top-down attention modulates interactions between posterior visual areas of the human brain.…”

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confidence: 99%

Top-down attention switches coupling between low-level and high-level areas of human visual cortex

Al-Aidroos

Said

Turk‐Browne

2012

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

172

217

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Top-down attention is an essential cognitive ability, allowing our finite brains to process complex natural environments by prioritizing information relevant to our goals. Previous evidence suggests that top-down attention operates by modulating stimulus-evoked neural activity within visual areas specialized for processing goal-relevant information. We show that top-down attention also has a separate influence on the background coupling between visual areas: adopting different attentional goals resulted in specific patterns of noise correlations in the visual system, whereby intrinsic activity in the same set of low-level areas was shared with only those high-level areas relevant to the current goal. These changes occurred independently of evoked activity, persisted without visual stimulation, and predicted behavioral success in deploying attention better than the modulation of evoked activity. This attentional switching of background connectivity suggests that attention may help synchronize different levels of the visual processing hierarchy, forming statedependent functional pathways in human visual cortex to prioritize goal-relevant information.category selectivity | functional MRI | goal-directed attention | retinotopic occipital cortex | ventral temporal cortex T he ventral visual stream, the neural substrate of object perception (1), is organized hierarchically. At early stages, occipital cortex decomposes visual images into simple features, such as form and orientation (2). At later stages, ventral temporal cortex combines these features into complex objects, such as faces and scenes (3). Although this hierarchy is hard-wired (4), human vision is flexible: our goals and intentions determine what we see via top-down attention (5). How does top-down attention prioritize goal-relevant information in the ventral visual stream?The conventional answer is that attention prioritizes certain information by enhancing evoked responses in cortical areas that represent this information. For example, when attending to faces (e.g., when looking for a friend in a crowd, or in our study, monitoring for a repeated face in a stream of composite images that contain both a face and a distracting scene), the response of the fusiform face area (FFA) to faces is enhanced; in contrast, when attending to scenes (e.g., when looking for a restaurant in a new town, or in our study, monitoring for a repeated scene in the composite images), the response of the parahippocampal place area (PPA) to scenes is enhanced (6). This attentional modulation is interpreted as resulting from top-down selection of goal-relevant information and relative inhibition of goal-irrelevant information. Similar effects have been observed throughout visual cortex and with diverse methodologies, including positron emission tomography (7), functional magnetic resonance imaging (fMRI) (6,8), and single-cell recordings (9, 10). By strengthening representations, top-down attention may ensure that goal-relevant information competes better against goal-irrelevant in...

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Phase Locking of Single Neuron Activity to Theta Oscillations during Working Memory in Monkey Extrastriate Visual Cortex

Cited by 364 publications

References 53 publications

Inferring Spike Trains From Local Field Potentials

Inferring Spike Trains From Local Field Potentials

Lack of the metabotropic glutamate receptor subtype 7 selectively modulates Theta rhythm and working memory

Top-down attention switches coupling between low-level and high-level areas of human visual cortex

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