Receptive Field Positions in Area MT during Slow Eye Movements

Hartmann, Till S.; Bremmer, Frank; Albright, Thomas D.; Krekelberg, Bart

doi:10.1523/jneurosci.5590-10.2011

Cited by 28 publications

(23 citation statements)

References 49 publications

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“…We next asked whether delivery of the reward is also represented in the activity of V1, POR, and LA →POR neurons. To isolate non-visually evoked, task-related responses, we exploited the trial-to-trial variability in the onset of lick responses to train a general linear model (GLM; Hartmann et al, 2011; Pinto and Dan, 2015) to estimate lick-, reward- and false alarm-related changes in neuronal activity. In all areas, we found examples of non-visually-responsive cells that increased their activity only at the time of Ensure delivery (Figure 8A, LA →POR axon) or at the onset of licking (Figure 8B, V1 cell body).…”

Section: Resultsmentioning

confidence: 99%

Hunger-Dependent Enhancement of Food Cue Responses in Mouse Postrhinal Cortex and Lateral Amygdala

Burgess

Ramesh

Sugden

et al. 2016

Neuron

161

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Summary The needs of the body can direct behavioral and neural processing towards motivationally relevant sensory cues. For example, human imaging studies have consistently found specific cortical areas with biased responses to food-associated visual cues in hungry subjects, but not in sated subjects. To obtain a cellular-level understanding of these hunger-dependent cortical response biases, we performed chronic two-photon calcium imaging in postrhinal association cortex (POR) and primary visual cortex (V1) of behaving mice. As in humans, neurons in mouse POR, but not V1, exhibited biases towards food-associated cues that were abolished by satiety. This emergent bias was mirrored by the innervation pattern of amygdalo-cortical feedback axons. Strikingly, these axons exhibited even stronger food cue biases and sensitivity to hunger state and trial history. These findings highlight a direct pathway by which the lateral amygdala may contribute to state-dependent cortical processing of motivationally relevant sensory cues.

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Section: Resultsmentioning

confidence: 99%

Hunger-Dependent Enhancement of Food Cue Responses in Mouse Postrhinal Cortex and Lateral Amygdala

Burgess

Ramesh

Sugden

et al. 2016

Neuron

161

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“…11). This is unlikely to have resulted from a preparatory remapping of the RFs in MT, which do not change with eye movements (Hartmann et al 2011;Inaba and Kawano 2014;Ong and Bisley 2011), but the RF in other areas can shift before eye movements (Duhamel et al 1992). Thus, as LFP activity can resemble the input to an area, late MT LFPs may have reflected the preparatory activity in downstream areas prior to the lever release.…”

Section: Discussionmentioning

confidence: 99%

Dynamics of the functional link between area MT LFPs and motion detection

Smith

Beliveau

Schoen

et al. 2015

Journal of Neurophysiology

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-The evolution of a visually guided perceptual decision results from multiple neural processes, and recent work suggests that signals with different neural origins are reflected in separate frequency bands of the cortical local field potential (LFP). Spike activity and LFPs in the middle temporal area (MT) have a functional link with the perception of motion stimuli (referred to as neural-behavioral correlation). To cast light on the different neural origins that underlie this functional link, we compared the temporal dynamics of the neural-behavioral correlations of MT spikes and LFPs. Wide-band activity was simultaneously recorded from two locations of MT from monkeys performing a threshold, two-stimuli, motion pulse detection task. Shortly after the motion pulse occurred, we found that high-gamma (100 -200 Hz) LFPs had a fast, positive correlation with detection performance that was similar to that of the spike response. Beta (10 -30 Hz) LFPs were negatively correlated with detection performance, but their dynamics were much slower, peaked late, and did not depend on stimulus configuration or reaction time. A late change in the correlation of all LFPs across the two recording electrodes suggests that a common input arrived at both MT locations prior to the behavioral response. Our results support a framework in which early high-gamma LFPs likely reflected fast, bottom-up, sensory processing that was causally linked to perception of the motion pulse. In comparison, late-arriving beta and highgamma LFPs likely reflected slower, top-down, sources of neuralbehavioral correlation that originated after the perception of the motion pulse.behavior; cortex; local field potential; MT; vision VISUALLY GUIDED DECISIONS involve multiple neural components, such as sensory and evaluative stages (Gold and Shadlen 2007). But when and how do different neural components make their contribution? This question is typically studied by measuring the trial-by-trial correlation between cortical spiking and perceptual behavior (Parker and Newsome 1998). Interpreting these neural-behavioral correlations, however, is difficult because they do not tell us whether fluctuations in neural activity directly produced fluctuations in perception. Thus additional data are needed to better understand and model the causality behind observed neural-behavioral correlations.Recent efforts have focused on the local field potential (LFP) and suggest that distinct neurophysiological processes can be measured from different LFP frequency bands (Bastos et al. 2015;Katzner et al. 2009;Kopell et al. 2010;Siegel et al. 2012). Gamma-band LFPs are thought to carry stimulus information (Belitski et al. 2010) and reflect the synaptic inputs from earlier stages (Khawaja et al. 2009) and the activity of local neurons (Ray and Maunsell 2011a), while beta-band LFPs may reflect intercortical feedback (Saalmann et al. 2007). Correspondingly, attention increases gamma LFP power in a manner similar to that of local spiking activity, while beta power is attenuated (Khaya...

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“…Trials in which fixation was not maintained within an invisible 2 ϫ 2-deg box were discarded. The receptive field was mapped using automated methods (Hartmann et al 2011;Krekelberg and Albright 2005) and used to center the stimulus on the receptive field. We first mapped the direction tuning of the cells with the small and large gratings moving in 1 of 16 equally spaced directions, presented for 1 s. This provided us with the preadaptation tuning curve and was used to select the adapter direction.…”

Section: Methodsmentioning

confidence: 99%

Similar adaptation effects in primary visual cortex and area MT of the macaque monkey under matched stimulus conditions

Patterson

Duijnhouwer

Wissig

et al. 2014

Journal of Neurophysiology

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Patterson CA, Duijnhouwer J, Wissig SC, Krekelberg B, Kohn A. Similar adaptation effects in primary visual cortex and area MT of the macaque monkey under matched stimulus conditions. J Neurophysiol 111: 1203-1213, 2014. First published December 26, 2013 doi:10.1152/jn.00030.2013.-Recent stimulus history, or adaptation, can alter neuronal response properties. Adaptation effects have been characterized in a number of visually responsive structures, from the retina to higher visual cortex. However, it remains unclear whether adaptation effects across stages of the visual system take a similar form in response to a particular sensory event. This is because studies typically probe a single structure or cortical area, using a stimulus ensemble chosen to provide potent drive to the cells of interest. Here we adopt an alternative approach and compare adaptation effects in primary visual cortex (V1) and area MT using identical stimulus ensembles. Previous work has suggested these areas adjust to recent stimulus drive in distinct ways. We show that this is not the case: adaptation effects in V1 and MT can involve weak or strong loss of responsivity and shifts in neuronal preference toward or away from the adapter, depending on stimulus size and adaptation duration. For a particular stimulus size and adaptation duration, however, effects are similar in nature and magnitude in V1 and MT. We also show that adaptation effects in MT of awake animals depend strongly on stimulus size. Our results suggest that the strategies for adjusting to recent stimulus history depend more strongly on adaptation duration and stimulus size than on the cortical area. Moreover, they indicate that different levels of the visual system adapt similarly to recent sensory experience. surround suppression; adaptation duration; motion processing; plasticity; V1 ADAPTATION, the stimulus history of the preceding hundreds of milliseconds to minutes, can profoundly change neuronal response properties. Adaptation effects have been characterized in the retina (e.g., Baccus and Meister 2002;Brown and

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Receptive Field Positions in Area MT during Slow Eye Movements

Cited by 28 publications

References 49 publications

Hunger-Dependent Enhancement of Food Cue Responses in Mouse Postrhinal Cortex and Lateral Amygdala

Hunger-Dependent Enhancement of Food Cue Responses in Mouse Postrhinal Cortex and Lateral Amygdala

Dynamics of the functional link between area MT LFPs and motion detection

Similar adaptation effects in primary visual cortex and area MT of the macaque monkey under matched stimulus conditions

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