Spatiotemporal Effects of Microstimulation in Rat Neocortex: A Parametric Study Using Multielectrode Recordings

Butovas, Sergejus; Schwarz, Cornelius

doi:10.1152/jn.00245.2003

Cited by 224 publications

(268 citation statements)

References 83 publications

Supporting

Mentioning

227

Contrasting

Unclassified

Order By: Relevance

“…Orthodromic effects occur either by the direct or by transsynaptic activation of projection neurons with cell bodies in the area that is stimulated. At the current levels used by us, most neurons are stimulated transsynaptically (68). Accordingly, previous studies demonstrated that orthodromic stimulation effects are many times stronger than antidromic effects even between areas with strong direct projections (62,70,71).…”

Section: Discussionmentioning

confidence: 97%

“…To our knowledge, our electrical microstimulation experiments provide the first causal evidence that feedforward processing induces γ-oscillations in a higher visual area and that feedback causes α-activity in a lower area. We used electrode arrays for microstimulation, positioned 1 or 1.5 mm below the cortical surface; they were presumably in layers 4 or 5, but the effects of microstimulation on neuronal activity are relatively homogeneous across cortical depth (67,68). Microstimulation activates axons in the vicinity of the electrode tip (68,69) and can cause orthodromic and antidromic stimulation effects in another area.…”

Section: Discussionmentioning

confidence: 99%

“…We used electrode arrays for microstimulation, positioned 1 or 1.5 mm below the cortical surface; they were presumably in layers 4 or 5, but the effects of microstimulation on neuronal activity are relatively homogeneous across cortical depth (67,68). Microstimulation activates axons in the vicinity of the electrode tip (68,69) and can cause orthodromic and antidromic stimulation effects in another area. Antidromic effects occur if axon terminals of projection neurons are stimulated and action potentials travel back to their cell-bodies in another area.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex

Kerkoerle

Self

Dagnino

et al. 2014

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

875

138

776

View full text Add to dashboard Cite

This Feature Article is part of a series identified by the Editorial Board as reporting findings of exceptional significance.Edited by Terrence J. Sejnowski, Salk Institute for Biological Studies, La Jolla, CA, and approved August 8, 2014 (received for review February 22, 2014) Cognitive functions rely on the coordinated activity of neurons in many brain regions, but the interactions between cortical areas are not yet well understood. Here we investigated whether lowfrequency (α) and high-frequency (γ) oscillations characterize different directions of information flow in monkey visual cortex. We recorded from all layers of the primary visual cortex (V1) and found that γ-waves are initiated in input layer 4 and propagate to the deep and superficial layers of cortex, whereas α-waves propagate in the opposite direction. Simultaneous recordings from V1 and downstream area V4 confirmed that γ-and α-waves propagate in the feedforward and feedback direction, respectively. Microstimulation in V1 elicited γ-oscillations in V4, whereas microstimulation in V4 elicited α-oscillations in V1, thus providing causal evidence for the opposite propagation of these rhythms. Furthermore, blocking NMDA receptors, thought to be involved in feedback processing, suppressed α while boosting γ. These results provide new insights into the relation between brain rhythms and cognition.neuronal synchronization | attention | perceptual organization | phase coherence | Granger causality A reas of the visual cortex are arranged hierarchically, with low-level areas representing simple features and higher areas representing the more complex aspects of the visual world (1, 2). Neurons in many visual areas are coactive during the perception of a visual stimulus and it is difficult to disentangle the influences of lower areas onto higher areas from the effects that go in the opposite direction (3). Studies of visual cognition could benefit enormously from markers of cortical activity that distinguish between feedforward and feedback effects. One such putative marker is cortical oscillatory activity, because oscillations of different frequencies have been proposed to propagate either in feedforward or in the feedback direction (4, 5), but experimental evidence for this view is sparse (6).Low-frequency rhythms, like the α-rhythm-which is particularly pronounced in the visual cortex-have been proposed to characterize spontaneous activity (7,8) as the α-rhythm increases when the subject closes the eyes (9). More recent observations have also implicated α-oscillations in the active suppression of irrelevant, unattended information (10, 11). In contrast, the high-frequency γ-rhythm increases if visual stimuli are presented, and in particular if they are task-relevant (12, 13). One influential hypothesis has been that γ-oscillations play a role in feature binding (14), but later studies cast doubt on this proposal (15,16). A more recent hypothesis holds that γ-oscillations facilitate the communication between cortical areas (17), but both evidence in fa...

show abstract

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex

Kerkoerle

Self

Dagnino

et al. 2014

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

875

138

776

View full text Add to dashboard Cite

show abstract

“…Stimulation trains consisted of 10-20 µA biphasic current pulses of 300 µs duration at a rate of 200 Hz. These levels are thought to directly activate neurons within an approximately 100 µm radius of the electrode tip 46 , but indirect activation of neural elements may increase this spread 47 . We applied microstimulation during the entire duration of the motion stimulus on a randomly chosen half of the trials.…”

Section: Electrophysiologymentioning

confidence: 99%

Microstimulation of macaque area LIP affects decision-making in a motion discrimination task

2006

View full text Add to dashboard Cite

A central goal of cognitive neuroscience is to elucidate the neural mechanisms underlying decisionmaking. Recent physiological studies suggest that neurons in association areas may be involved in this process. To test this, we measured the effects of electrical microstimulation in the lateral intraparietal area (LIP) while monkeys performed a reaction-time motion discrimination task with a saccadic response. In each experiment, we identified a cluster of LIP cells with overlapping response fields (RFs) and sustained activity during memory-guided saccades. Microstimulation of this cluster caused an increase in the proportion of choices to the RF of the stimulated neurons. Choices toward the stimulated RF were faster with microstimulation, while choices in the opposite direction were slower. Microstimulation never directly evoked saccades, nor did it change reaction times in a simple saccade task. These results demonstrate that the discharge of LIP neurons is causally related to decision formation on the discrimination task.Much progress has been made in understanding the neurobiology of decision-making by tracing the neural events that link sensory processing to a choice of action in monkeys 1-4 . For example, to decide whether a pattern of random dots is moving to the left or right, the brain must represent the motion information in the visual cortex, interpret this information as evidence for one or the other direction, and eventually commit to a choice, indicated by some action. Through a combination of recording, lesion, and microstimulation experiments, the activity of directionselective neurons in area MT has been shown to represent an important source of the sensory evidence upon which such a decision about direction is based [5][6][7][8] . This raises the question of how that representation is converted into a categorical decision.When performing the motion discrimination task, monkeys improve in accuracy when given more time to view the stimulus 6,9 . Furthermore, in a reaction-time version of the task, stronger motion leads to both faster and more accurate decisions 10 . These findings can be explained by a simple mechanism whereby momentary sensory evidence is accumulated over time toward a criterion level, which in turn yields a commitment to a proposition and ultimately an action.A neural correlate of this process has been described in the macaque parietal cortex 10,11 . Many LIP neurons respond when visual stimuli are presented at a specific location in space or when monkeys intend to make a saccade to that same location; thus, they have combined sensory and motor RFs 12,13 . When monkeys indicate decisions about direction of motion with an eye movement, LIP neurons increase or decrease their firing as evidence accumulates in favor of or against the choice associated with the target in their RF 10 . This rise and fall in activity

show abstract

“…However, advanced neuroscience capable of studying cellular interactions in complex networks can be accelerated with selective activation or silencing of neurons of specific types. This feat cannot be achieved easily by electrical stimulation due to its lack of spatial resolution, non-specific stimulation, and the inability to silence neurons 148 .…”

Section: Stimulating Brain Activity Introduction To Optogeneticsmentioning

confidence: 99%

State-of-the-art MEMS and microsystem tools for brain research

et al. 2017

View full text Add to dashboard Cite

Mapping brain activity has received growing worldwide interest because it is expected to improve disease treatment and allow for the development of important neuromorphic computational methods. MEMS and microsystems are expected to continue to offer new and exciting solutions to meet the need for high-density, high-fidelity neural interfaces. Herein, the state-of-the-art in recording and stimulation tools for brain research is reviewed, and some of the most significant technology trends shaping the field of neurotechnology are discussed.

show abstract

Spatiotemporal Effects of Microstimulation in Rat Neocortex: A Parametric Study Using Multielectrode Recordings

Cited by 224 publications

References 83 publications

Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex

Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex

Microstimulation of macaque area LIP affects decision-making in a motion discrimination task

State-of-the-art MEMS and microsystem tools for brain research

Contact Info

Product

Resources

About