Mark H. Histed

Direct Activation of Sparse, Distributed Populations of Cortical Neurons by Electrical Microstimulation

For over a century, electrical microstimulation has been the most direct method for causally linking brain function with behavior. Despite this long history, it is still unclear how the activity of neural populations is affected by stimulation. For example, there is still no consensus on where activated cells lie or on the extent to which neural processes such as passing axons near the electrode are also activated. Past studies of this question have proven difficult because microstimulation interferes with electrophysiological recordings, which in any case provide only coarse information about the location of activated cells. We used two-photon calcium imaging, an optical method, to circumvent these hurdles. We found that microstimulation sparsely activates neurons around the electrode, sometimes as far as millimeters away, even at low currents. Our results indicate that the pattern of activated neurons likely arises from the direct activation of axons in a volume tens of microns in diameter.

Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex

Many thousands of cortical neurons are activated by any single sensory stimulus, but the organization of these populations is poorly understood. For example, are neurons in mouse visual cortex—whose preferred orientations are arranged randomly—organized with respect to other response properties? Using high-speed in vivo two-photon calcium imaging, we characterized the receptive fields of up to 100 excitatory and inhibitory neurons in a 200 μm imaged plane. Inhibitory neurons had nonlinearly summating, complex-like receptive fields and were weakly tuned for orientation. Excitatory neurons had linear, simple receptive fields that can be studied with noise stimuli and system identification methods. We developed a wavelet stimulus that evoked rich population responses and yielded the detailed spatial receptive fields of most excitatory neurons in a plane. Receptive fields and visual responses were locally highly diverse, with nearby neurons having largely dissimilar receptive fields and response time courses. Receptive-field diversity was consistent with a nearly random sampling of orientation, spatial phase, and retinotopic position. Retinotopic positions varied locally on average by approximately half the receptive-field size. Nonetheless, the retinotopic progression across the cortex could be demonstrated at the scale of 100 μm, with a magnification of ∼10 μm/°. Receptive-field and response similarity were in register, decreasing by 50% over a distance of 200 μm. Together, the results indicate considerable randomness in local populations of mouse visual cortical neurons, with retinotopy as the principal source of organization at the scale of hundreds of micrometers.

Similarity of Visual Selectivity among Clonally Related Neurons in Visual Cortex

Neurons in rodent visual cortex are organized in a salt-and-pepper fashion for orientation selectivity, but it is still unknown how this functional architecture develops. A recent study reported that the progeny of single cortical progenitor cells are preferentially connected in the postnatal cortex. If these neurons acquire similar selectivity through their connections, a salt-and-pepper organization may be generated, because neurons derived from different progenitors are intermingled in rodents. Here we investigated whether clonally related cells have similar preferred orientation by using a transgenic mouse, which labels all the progeny of single cortical progenitor cells. We found that preferred orientations of clonally related cells are similar to each other, suggesting that cell lineage is involved in the development of response selectivity of neurons in the cortex. However, not all clonally related cells share response selectivity, suggesting that cell lineage is not the only determinant of response selectivity.

Insights into cortical mechanisms of behavior from microstimulation experiments.

Even the simplest behaviors depend on a large number of neurons that are distributed across many brain regions. Because electrical microstimulation can change the activity of localized subsets of neurons, it has provided valuable evidence that specific neurons contribute to particular behaviors. Here we review what has been learned about cortical function from behavioral studies using microstimulation in animals and humans. Experiments that examine how microstimulation affects the perception of stimuli have shown that the effects of microstimulation are usually highly specific and can be related to the stimuli preferred by neurons at the stimulated site. Experiments that ask subjects to detect cortical microstimulation in the absence of other stimuli have provided further insights. Although subjects typically can detect microstimulation of primary sensory or motor cortex, they are generally unable to detect stimulation of most of cortex without extensive practice. With practice, however, stimulation of any part of cortex can become detected. These training effects suggest that some patterns of cortical activity cannot be readily accessed to guide behavior, but that the adult brain retains enough plasticity to learn to process novel patterns of neuronal activity arising anywhere in cortex.

Mouse Primary Visual Cortex Is Used to Detect Both Orientation and Contrast Changes

In mammals, the lateral geniculate nucleus (LGN) and the superior colliculus (SC) are the major targets of visual inputs from the retina. The LGN projects mainly to primary visual cortex (V1) while the SC targets the thalamus and brainstem, providing two potential pathways for processing visual inputs. Indeed, cortical lesion experiments in rodents have yielded mixed results, leading to the hypothesis that performance of simple visual behaviors may involve computations performed entirely by this subcortical pathway through the SC. However, these previous experiments have been limited by both their assays of behavioral performance and their use of lesions to change cortical activity. To determine the contribution of V1 to these tasks, we trained mice to perform threshold detection tasks in which they reported changes in either the contrast or orientation of visual stimuli. We then reversibly inhibited V1 by optogenetically activating parvalbumin-expressing inhibitory neurons with channelrhodopsin-2. We found that suppressing activity in V1 substantially impaired performance in visual detection tasks. The behavioral deficit depended on the retinotopic position of the visual stimulus, confirming that the effect was due to the specific suppression of the visually driven V1 neurons. Behavioral effects were seen with only moderate changes in neuronal activity, as inactivation that raised neuronal contrast thresholds by a median of only 14% was associated with a doubling of behavioral contrast detection threshold. Thus, detection of changes in either orientation or contrast is dependent on, and highly sensitive to, the activity of neurons in V1.

Psychophysical measurement of contrast sensitivity in the behaving mouse

To understand how activity in mammalian neural circuits controls behavior, the mouse is a promising model system due to the convergence of genetic, optical, and physiological methods. The ability to control and quantify behavior precisely is also essential for these studies. We developed an operant visual detection paradigm to make visual psychophysical measurements: head-fixed mice make responses by pressing a lever. We designed this task to permit neurophysiological studies of behavior in cerebral cortex, where activity is variable from trial to trial and neurons encode many types of information simultaneously. To study neural responses in the face of this complexity, we trained mice to do a task where they perform hundreds of trials daily and perceptual thresholds can be measured. We used this task to measure both visual acuity and the minimum detectable contrast in behaving mice. We found that the mouse contrast response function is similar in shape to other species. They can detect low-contrast stimuli, with a peak contrast threshold of 2%, equivalent to ∼15° eccentric in human vision. Mouse acuity is modest, with an upper limit near 0.5 cycles/°, consistent with prior data.

Cortical neural populations can guide behavior by integrating inputs linearly, independent of synchrony

Significance The brain performs computations by transforming sensory inputs to make decisions. We study these neuronal computations in the mouse, one of the smallest animals with a cerebral cortex, the part of the human brain that controls complex behavior. We find animals’ behavior can be insensitive to the timing of cortical inputs, depending only on total spike count, even though individual neurons are sensitive to timing. Thus, the cortex can integrate input linearly, or place equal weight on inputs regardless of their arrival time. This emergent linear network behavior may arise from fluctuations in membrane potential generated by background network activity. Brain diseases may arise from dysfunction of these network properties, perhaps by damaging the mechanisms that create this background noise. Neurons are sensitive to the relative timing of inputs, both because several inputs must coincide to reach spike threshold and because active dendritic mechanisms can amplify synchronous inputs. To determine if input synchrony can influence behavior, we trained mice to report activation of excitatory neurons in visual cortex using channelrhodopsin-2. We used light pulses that varied in duration from a few milliseconds to 100 ms and measured neuronal responses and animals’ detection ability. We found detection performance was well predicted by the total amount of light delivered. Short pulses provided no behavioral advantage, even when they concentrated evoked spikes into an interval a few milliseconds long. Arranging pulses into trains of varying frequency from beta to gamma also produced no behavioral advantage. Light intensities required to drive behavior were low (at low intensities, channelrhodopsin-2 conductance varies linearly with intensity), and the accompanying changes in firing rate were small (over 100 ms, average change: 1.1 spikes per s). Firing rate changes varied linearly with pulse intensity and duration, and behavior was predicted by total spike count independent of temporal arrangement. Thus, animals’ detection performance reflected the linear integration of total input over 100 ms. This behavioral linearity despite neurons’ nonlinearities can be explained by a population code using noisy neurons. Ongoing background activity creates probabilistic spiking, allowing weak inputs to change spike probability linearly, with little amplification of coincident input. Summing across a population then yields a total spike count that weights inputs equally, regardless of their arrival time.

Different inhibitory interneuron cell classes make distinct contributions to visual perception

While recent work has revealed how different inhibitory interneurons influence cortical responses to sensory stimuli, little is known about how their activity contributes to sensory perception. Here, we optogenetically stimulated different genetically defined interneurons (parvalbumin (PV), somatostatin (SST), vasoactive intestinal peptide (VIP)) in visual cortex (V1) of mice working at threshold in contrast increment or decrement detection tasks. The visual stimulus was paired with optogenetic stimulation to assess how enhancing V1 inhibitory neuron activity synchronously during cortical responses altered task performance. PV or SST activation impaired, while VIP stimulation improved, contrast increment detection. Notably, PV or SST stimulation also impaired contrast decrement detection, when opsin-evoked inhibition would exaggerate stimulus-evoked decrements in firing rate, and thus might improve performance. The impairment produced by PV or SST stimulation persisted throughout many weeks of testing. In contrast mice learned to reliably detect VIP activation in the absence of natural visual stimulation. Thus, different inhibitory signals make distinct contributions to visual contrast perception.

The 8th annual computational and systems neuroscience (Cosyne) meeting.

The 8th annual Computational and Systems Neuroscience meeting (Cosyne) was held February 24-27, 2011 in Salt Lake City, Utah (abstracts are freely available online: http://www.cosyne.org/c/index.php?title=Cosyne2011_Program). Cosyne brings together experimental and theoretical approaches to systems neuroscience, with the goal of understanding neurons, neural assemblies, and the perceptual, cognitive and behavioral functions they mediate.