We are searching data for your request:
Upon completion, a link will appear to access the found materials.
I'm new to neuroscience research and came across a term called negative spikes (sometimes also used in conjunction with terms biphasic spikes or positive-negative spikes), but could not find what it meant from scientific papers. Can a spike occur in a negative direction (hyperpolarization from the resting potential first, followed by depolarization) or does this term mean something else entirely?
Intracellular recordings of action potentials always show the same format with which you are familiar. There is polarisation which the stimulus reduces, a threshold is reached, there is a positive spike, then repolarisation, hyperpolarisation, a refractory period an a return to the baseline polarisation.
The term "negative spike" applies to extracellular recordings. These measure the potential between a point close to but outside the cell and a reference point. The inflow of cations into the cell causes a drop in extracellular potential, which appears as a negative spike in the recording.
Antagonistic negative and positive neurons of the basolateral amygdala
The basolateral amygdala (BLA) is a site of convergence of negative and positive stimuli and is critical for emotional behaviors and associations. However, the neural substrate for negative and positive behaviors and relationship between negative and positive representations in the basolateral amygdala are unknown. Here we identify two genetically distinct, spatially segregated populations of excitatory neurons in the mouse BLA that participate in valence-specific behaviors and are connected through mutual inhibition. These results identify a genetically defined neural circuit for the antagonistic control of emotional behaviors and memories.
Figure 1. Activity-dependent transcriptional profiling of BLA…
Figure 1. Activity-dependent transcriptional profiling of BLA neurons
a, Viral-based genetic scheme for activity-dependent transcriptional…
Figure 2. Rspo2 + and Ppp1r1b +…
Figure 2. Rspo2 + and Ppp1r1b + BLA neurons define spatially segregated populations of BLA…
Figure 3. Rspo2 + and Ppp1r1b +…
Figure 3. Rspo2 + and Ppp1r1b + BLA neurons are activated by valence-specific stimuli
Figure 4. Rspo2 + and Ppp1r1b +…
Figure 4. Rspo2 + and Ppp1r1b + BLA neurons participate in valence-specific behaviors
a, Optogenetically targeting Rspo2…
Figure 5. Rpso2 + and Ppp1r1b +…
Figure 5. Rpso2 + and Ppp1r1b + BLA neurons antagonize valence-specific behaviors
a, Scheme of activation of…
Figure 6. Rspo2 + and Ppp1r1b +…
Figure 6. Rspo2 + and Ppp1r1b + BLA neurons establish reciprocal inhibitory connections
Figure 7. Rspo2 + and Ppp1r1b +…
Figure 7. Rspo2 + and Ppp1r1b + BLA neurons project to distinct amygdaloid nuclei and…
Get full journal access for 1 year
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
We have shown that synaptically evoked dendritic spikes in Purkinje cells serve a dual role: They enhance axonal output on brief timescales but paradoxically inhibit average axonal firing rates over longer timescales. This inhibitory effect presents a striking contrast to cortical pyramidal cells, where dendritic spikes are purely excitatory, increasing the gain of synaptic input. We demonstrate that the mechanism of this paradoxical inhibition caused by dendritic spikes in Purkinje cells involves the activation of dendritic calcium-activated BK-type calcium channels, which balance the inward current provided by calcium channel activation. These results indicate that the complement of dendritic voltage-gated conductances determines the functional signature of dendritic spikes. This signature is cell-type specific and may reflect the opposite polarity of neuronal output in pyramidal cells and Purkinje cells.
Dendritic Spikes Trigger Pauses in Axonal Output.
We demonstrate that in Purkinje cells, dendritic spikes exert a dual role on axonal output. On short timescales, they enhance AP firing, triggering a brief burst of spikes. This effect is similar to pyramidal cells, where dendritic spikes are also associated with enhanced axonal AP generation (1, 6, 7), often leading to bursts of spikes (5, 6). In contrast, on longer timescales, the dendritic spike leads to a prolonged pause in spontaneous firing following the parallel fiber synaptic input, an inhibitory effect that cancels out the effect of the burst of spikes on the average axonal firing rate. Thus, the net effect of dendritic spikes on average axonal output rate is neutral. When trains of synaptic inputs activate multiple dendritic spikes, this inhibitory effect can summate, leading to the clamping of the output firing rate at a fixed value. Interestingly, spike synchronization (a timing code) and spike rate modification (a rate code) have been shown to relay different information in another motor area, the primary motor cortex of macaque monkeys (44), suggesting the two coding strategies can coexist and complement each other. The climbing fiber input in Purkinje cells also triggers dendritic spikes, which have recently been shown to regulate the postcomplex spike pause in axonal firing (14). However, the dendritic spikes activated by the complex spike are global, and their effect on axonal output is weakened by the strong synaptic and intrinsic conductances active during the complex spike. In contrast, here we show that dendritic spikes triggered by single parallel fiber stimuli, which produce highly localized spikes (13), can still produce a significant effect on axonal spiking, both in terms of burst generation and the subsequent pauses. This pausing effect of dendritic spikes, an intrinsic counterpart to feed-forward inhibition, is particularly significant given that they are superimposed on top of the high spontaneous firing rate of Purkinje cells (28, 45, 46), and may contribute to the pauses in Purkinje cell spiking seen in vivo (45, 47) and following synchronous PF stimulation in vitro (48).
Relative Contribution of Voltage-Gated Conductances Driven by Dendritic Spikes.
What is the mechanism driving the enhanced pause following a dendritic spike and the clamping effect produced during multiple dendritic spikes? We demonstrate that a selective blocker of BK-type calcium-activated potassium channels, which strongly reduces the dendritic AHP following a dendritic spike (13, 36), can prevent the clamping effect. This result indicates that the outward current mediated by BK channels is sufficiently strong to counteract the net effect of the inward current delivered by activation of P-type calcium channels during the dendritic spike. This finding is consistent with voltage clamp experiments in isolated Purkinje cell somata showing that the net effect of blocking calcium channels is to remove an outward current (49), indicating that calcium-activated potassium currents predominate over calcium currents (at least in the somatic membrane). To most effectively influence the shape of the dendritic spike, and its afterhyperpolarization, the BK channels must be localized close to the source of the calcium entry triggered by the dendritic spikes, i.e., in the dendrite this assumption is consistent with anatomical (50) and electrophysiological evidence for the dendritic location of BK channels in Purkinje cells (51). Once the threshold for dendritic spiking is reached, this balancing of inward and outward conductances remains effective over a wide range of input strengths, producing a flat I/O curve. Thus, the relative density and dynamics of activation and inactivation of calcium channels and BK-type channels (and possibly other conductances refs. 39 and 52–57) must be carefully calibrated to produce this robust balancing effect, which is independent of input strength. The balancing of inward and outward currents driven by a dendritic spike appears to be a distinctive signature of Purkinje cells, because in pyramidal cells, inward currents appear to predominate and pausing is not observed.
Consequences for Cerebellar Function.
Our results are consistent with two modes of integration of parallel fiber synaptic input in cerebellar Purkinje cells. At low input strengths, the relationship between maximal firing frequency and parallel fiber input is linear (29, 33, 58), enabling the simplest possible encoding strategy for parallel fiber input strength. Dendritic properties may contribute to, but are not required for this linearity, because the f/I curve of Purkinje cells remains linear after the removal of the dendrites (59). Above threshold for generation of dendritic spikes, however, the f/I relationship becomes flat, with average firing rate remaining clamped at ≈220 Hz, independently of the input intensity. This clamping is in sharp contrast to pyramidal cells, where recruitment of dendritic voltage-gated calcium channels during dendritic synaptic input produces an increased gain of the f/I function (9). The clamping or saturation of the I/O curve at high levels of synaptic input can also be observed in pyramidal cell I/O curves, but it is thought to be due primarily to shunting by synaptic conductances. In contrast, Purkinje cells exhibit an intrinsic mechanism based on balanced voltage-gated conductances for regulating synaptic gain and limiting dynamic range at high input intensities. This rapid, real-time mechanism will complement other ways to limit output gain, such as feedforward inhibition (30), which is active over a wider range of input strengths, and retrograde endocannabinoid-dependent suppression of parallel fiber input (13), which provides negative feedback over longer timescales. Recent advances in calcium imaging (4) and whole-cell recording in awake, freely behaving animals (60) should eventually help make it possible to determine under which conditions this mechanism is called into action during behavior.
What is the functional purpose of the clamping effect of dendritic spikes on axonal output? Axonal spiking is energetically expensive (61 see also ref. 62), and given the high spontaneous firing rates exhibited by Purkinje cells, this intrinsically imposed ceiling on activity may represent an energy-saving measure. Furthermore, the close match between the firing rates at which dendritic spikes clamp somatic output and the maximal frequency for faithful transmission of spiking (41, 42) suggests that the clamping of axonal output may be required to maintain optimal transmission of spikes along the axon by obviating generation of spikes which cannot be transmitted.
Finally, the temporal dynamics of the axonal spiking pattern associated with dendritic spikes—a burst of APs followed by a pause—may also have important consequences for information transfer at the Purkinje cell to deep cerebellar nuclei (DCN) relay (47) by improving the discriminability of learned patterns in Purkinje cells (48) and producing an improved signal-to-noise at the synaptic connection with DCN neurons, due to the short-term dynamics of Purkinje cell synapses (63, 64). This effect will further be amplified by the summation of postsynaptic IPSPs (65) and consequently also the rebound excitability of DCN neurons (54, 66, 67). In this way, even though parallel fiber-triggered dendritic spikes experience marked attenuation toward the soma (13), they can still profoundly influence axonal output and its downstream consequences.
Negative spikes in neurons - Biology
Neurons & the Nervous System
The human nervous system consists of billions of nerve cells (or neurons) plus supporting (neuroglial) cells. Neurons are able to respond to stimuli (such as touch, sound, light, and so on), conduct impulses, and communicate with each other (and with other types of cells like muscle cells).
The nucleus of a neuron is located in the cell body. Extending out from the cell body are processes called dendrites and axons. These processes vary in number & relative length, but always serve to conduct impulses (with dendrites conducting impulses toward the cell body and axons conducting impulses away from the cell body).
Neurons can respond to stimuli and conduct impulses because a membrane potential is established across the cell membrane. In other words, there is an unequal distribution of ions (charged atoms) on the two sides of a nerve cell membrane. This can be illustrated with a voltmeter:
With one electrode placed inside a neuron and the other outside, the voltmeter is 'measuring' the difference in the distribution of ions on the inside versus the outside. And, in this example, the voltmeter reads -70 mV (mV = millivolts). In other words, the inside of the neuron is slightly negative relative to the outside. This difference is referred to as the Resting Membrane Potential. How is this potential established?
The membranes of all nerve cells have a potential difference across them, with the cell interior negative with respect to the exterior (a). In neurons, stimuli can alter this potential difference by opening sodium channels in the membrane. For example, neurotransmitters interact specifically with sodium channels (or gates). So sodium ions flow into the cell, reducing the voltage across the membrane.
Once the potential difference reaches a threshold voltage, the reduced voltage causes hundreds of sodium gates in that region of the membrane to open briefly. Sodium ions flood into the cell, completely depolarizing the membrane (b). This opens more voltage-gated ion channels in the adjacent membrane, and so a wave of depolarization courses along the cell &mdash the action potential.
As the action potential nears its peak, the sodium gates close, and potassium gates open, allowing ions to flow out of the cell to restore the normal potential of the membrane (c) (Gutkin and Ermentrout 2006).
Establishment of the Resting Membrane Potential
Membranes are polarized or, in other words, exhibit a RESTING MEMBRANE POTENTIAL. This means that there is an unequal distribution of ions (atoms with a positive or negative charge) on the two sides of the nerve cell membrane. This POTENTIAL generally measures about 70 millivolts (with the INSIDE of the membrane negative with respect to the outside). So, the RESTING MEMBRANE POTENTIAL is expressed as -70 mV, and the minus means that the inside is negative relative to (or compared to) the outside. It is called a RESTING potential because it occurs when a membrane is not being stimulated or conducting impulses (in other words, it's resting).
What factors contribute to this membrane potential?
Two ions are responsible: sodium (Na+) and potassium (K+). An unequal distribution of these two ions occurs on the two sides of a nerve cell membrane because carriers actively transport these two ions: sodium from the inside to the outside and potassium from the outside to the inside. As a result of this active transport mechanism (commonly referred to as the SODIUM - POTASSIUM PUMP), there is a higher concentration of sodium on the outside than the inside and a higher concentration of potassium on the inside than the outside (Animation: How the Sodium-Potassium Pump Works).
The Sodium-Potassium Pump
Used with permission of Gary Kaiser
The nerve cell membrane also contains special passageways for these two ions that are commonly referred to as GATES or CHANNELS. Thus, there are SODIUM GATES and POTASSIUM GATES. These gates represent the only way that these ions can diffuse through a nerve cell membrane. IN A RESTING NERVE CELL MEMBRANE, all the sodium gates are closed and some of the potassium gates are open. AS A RESULT, sodium cannot diffuse through the membrane & largely remains outside the membrane. HOWEVER, some potassium ions are able to diffuse out.
OVERALL, therefore, there are lots of positively charged potassium ions just inside the membrane and lots of positively charged sodium ions PLUS some potassium ions on the outside. THIS MEANS THAT THERE ARE MORE POSITIVE CHARGES ON THE OUTSIDE THAN ON THE INSIDE. In other words, there is an unequal distribution of ions or a resting membrane potential. This potential will be maintained until the membrane is disturbed or stimulated. Then, if it's a sufficiently strong stimulus, an action potential will occur.
Voltage sensing in a sodium ion channel. The voltage sensors in a sodium channels are charged 'paddles'
that move through the fluid membrane interior. Voltage sensors (two of which are shown here) are linked mechanically to
the channel's 'gate'. Each voltage sensor has four positive charges (amino acids) (Modified slightly from Sigworth 2003).
An action potential is a very rapid change in membrane potential that occurs when a nerve cell membrane is stimulated. Specifically, the membrane potential goes from the resting potential (typically -70 mV) to some positive value (typically about +30 mV) in a very short period of time (just a few milliseconds).
What causes this change in potential to occur? The stimulus causes the sodium gates (or channels) to open and, because there's more sodium on the outside than the inside of the membrane, sodium then diffuses rapidly into the nerve cell. All these positively-charged sodiums rushing in causes the membrane potential to become positive (the inside of the membrane is now positive relative to the outside). The sodium channels open only briefly, then close again.
The potassium channels then open, and, because there is more potassium inside the membrane than outside, positively-charged potassium ions diffuse out. As these positive ions go out, the inside of the membrane once again becomes negative with respect to the outside (Animation: Voltage-gated channels) .
Threshold stimulus & potential
- Action potentials occur only when the membrane in stimulated (depolarized) enough so that sodium channels open completely. The minimum stimulus needed to achieve an action potential is called the threshold stimulus.
- The threshold stimulus causes the membrane potential to become less negative (because a stimulus, no matter how small, causes a few sodium channels to open and allows some positively-charged sodium ions to diffuse in).
- If the membrane potential reaches the threshold potential (generally 5 - 15 mV less negative than the resting potential), the voltage-regulated sodium channels all open. Sodium ions rapidly diffuse inward, & depolarization occurs.
All-or-None Law - action potentials occur maximally or not at all. In other words, there's no such thing as a partial or weak action potential. Either the threshold potential is reached and an action potential occurs, or it isn't reached and no action potential occurs.
Impulse conduction - an impulse is simply the movement of action potentials along a nerve cell. Action potentials are localized (only affect a small area of nerve cell membrane). So, when one occurs, only a small area of membrane depolarizes (or 'reverses' potential). As a result, for a split second, areas of membrane adjacent to each other have opposite charges (the depolarized membrane is negative on the outside & positive on the inside, while the adjacent areas are still positive on the outside and negative on the inside). An electrical circuit (or 'mini-circuit') develops between these oppositely-charged areas (or, in other words, electrons flow between these areas). This 'mini-circuit' stimulates the adjacent area and, therefore, an action potential occurs. This process repeats itself and action potentials move down the nerve cell membrane. This 'movement' of action potentials is called an impulse.
- the speed of conduction is influenced by the presence or absence of myelin
- Neurons with myelin (or myelinated neurons) conduct impulses much faster than those without myelin.
The myelin sheath (blue) surrounding axons (yellow) is produced by glial cells (Schwann cells in the PNS, oligodendrocytes in the CNS). These cells produce large membranous extensions that ensheath the axons in successive layers that are then compacted by exclusion of cytoplasm (black) to form the myelin sheath. The thickness of the myelin sheath (the number of wraps around the axon) is proportional to the axon's diameter.
Myelination, the process by which glial cells ensheath the axons of neurons in layers of myelin, ensures the rapid conduction of electrical impulses in the nervous system. The formation of myelin sheaths is one of the most spectacular examples of cell-cell interaction and coordination in nature. Myelin sheaths are formed by the vast membranous extensions of glial cells: Schwann cells in the peripheral nervous system (PNS) and oligodendrocytes in the central nervous system (CNS). The axon is wrapped many times (like a Swiss roll) by these sheetlike membrane extensions to form the final myelin sheath, or internode. Internodes can be as long as 1 mm and are separated from their neighbors by a short gap (the node of Ranvier) of 1 micrometer. The concentration of voltage-dependent sodium channels in the axon membrane at the node, and the high electrical resistance of the multilayered myelin sheath, ensure that action potentials jump from node to node (a process termed "saltatory conduction") (ffrench-Constant 2004).
Schwann cells (or oligodendrocytes) are located at regular intervals along the process (axons and, for some neurons, dendrites) & so a section of a myelinated axon would look like this:
Between areas of myelin are non-myelinated areas called the nodes of Ranvier. Because fat (myelin) acts as an insulator, membrane coated with myelin will not conduct an impulse. So, in a myelinated neuron, action potentials only occur along the nodes and, therefore, impulses 'jump' over the areas of myelin - going from node to node in a process called saltatory conduction (with the word saltatory meaning 'jumping'):
Because the impulse 'jumps' over areas of myelin, an impulse travels much faster along a myelinated neuron than along a non-myelinated neuron.
Types of Neurons - the three main types of neurons are:
Multipolar neurons are so-named because they have many (multi-) processes that extend from the cell body: lots of dendrites plus a single axon. Functionally, these neurons are either motor (conducting impulses that will cause activity such as the contraction of muscles) or association (conducting impulses and permitting 'communication' between neurons within the central nervous system).
Unipolar neurons have one process from the cell body. However, that single, very short, process splits into longer processes (a dendrite plus an axon). Unipolar neurons are sensory neurons conducting impulses into the central nervous system.
Bipolar neurons have two processes - one axon & one dendrite. These neurons are also sensory. For example, bipolar neurons can be found in the retina of the eye.
Neuroglial, or glial, cells - general functions include:
1 - forming myelin sheaths
2 - protecting neurons (via phagocytosis)
3 - regulating the internal environment of neurons in the central nervous system
Synapse = point of impulse transmission between neurons impulses are transmitted from pre-synaptic neurons to post-synaptic neurons
Synapses usually occur between the axon of a pre-synaptic neuron & a dendrite or cell body of a post-synaptic neuron. At a synapse, the end of the axon is 'swollen' and referred to as an end bulb or synaptic knob. Within the end bulb are found lots of synaptic vesicles (which contain neurotransmitter chemicals) and mitochondria (which provide ATP to make more neurotransmitter). Between the end bulb and the dendrite (or cell body) of the post-synaptic neuron, there is a gap commonly referred to as the synaptic cleft. So, pre- and post-synaptic membranes do not actually come in contact. That means that the impulse cannot be transmitted directly. Rather, the impulse is transmitted by the release of chemicals called chemical transmitters (or neurotransmitters).
Micrograph of a synapse (Schikorski and Stevens 2001).
Post-synaptic membrane receptors
Structural features of a typical nerve cell (i.e., neuron) and synapse. This drawing shows the major components of a typical neuron, including the cell body with the nucleus the dendrites that receive signals from other neurons and the axon that relays nerve signals to other neurons at a specialized structure called a synapse. When the nerve signal reaches the synapse, it causes the release of chemical messengers (i.e., neurotransmitters) from storage vesicles. The neurotransmitters travel across a minute gap between the cells and then interact with protein molecules (i.e., receptors) located in the membrane surrounding the signal-receiving neuron. This interaction causes biochemical reactions that result in the generation, or prevention, of a new nerve signal, depending on the type of neuron, neurotransmitter, and receptor involved (Goodlett and Horn 2001).
When an impulse arrives at the end bulb, the end bulb membrane becomes more permeable to calcium. Calcium diffuses into the end bulb & activates enzymes that cause the synaptic vesicles to move toward the synaptic cleft. Some vesicles fuse with the membrane and release their neurotransmitter (a good example of exocytosis). The neurotransmitter molecules diffuse across the cleft and fit into receptor sites in the postsynaptic membrane. When these sites are filled, sodium channels open & permit an inward diffusion of sodium ions. This, of course, causes the membrane potential to become less negative (or, in other words, to approach the threshold potential). If enough neurotransmitter is released, and enough sodium channels are opened, then the membrane potential will reach threshold. If so, an action potential occurs and spreads along the membrane of the post-synaptic neuron (in other words, the impulse will be transmitted). Of course, if insufficient neurotransmitter is released, the impulse will not be transmitted.
Impulse transmission - The nerve impulse (action potential) travels down the presynaptic axon towards the synapse, where it activates voltage-gated calcium channels leading to calcium influx, which triggers the simultaneous release of neurotransmitter molecules from many synaptic vesicles by fusing the membranes of the vesicles to that of the nerve terminal. The neurotransmitter molecules diffuse across the synaptic cleft, bind briefly to receptors on the postsynaptic neuron to activate them, causing physiological responses that may be excitatory or inhibitory depending on the receptor. The neurotransmitter molecules are then either quickly pumped back into the presynaptic nerve terminal via transporters, are destroyed by enzymes near the receptors (e.g. breakdown of acetylcholine by cholinesterase), or diffuse into the surrounding area.
ffrench-Constant, C., H. Colognato, and R. J. M. Franklin. 2004. Neuroscience: the mysteries of myelin unwrapped. Science 304:688-689.
Goodlett, C.R., and K. H. Horn. 2001. Mechanisms of alcohol-induced damage to the developing nervous system. Alcohol Research & Health 25:175&ndash184.
Gutkin, B. and G. B. Ermentrout. 2006. Neuroscience: spikes too kinky in the cortex? Nature 440: 999-1000.
Sigworth, F. J. 2003. Structural biology: life's transistors. Nature 423:21-22.
Zhou, M., João H. Morais-Cabral, Sabine Mann and Roderick MacKinnon. 2001. Potassium channel receptor site for the inactivation gate and quaternary amine inhibitors. Nature 411:657-661.
Brain Areas Involved in Seeking Information About Bad Possibilities Identified
Summary:Study reveals specific neurons in the ventrolateral prefrontal cortex and anterior cingulate cortex that become active when people are faced with the decision to learn or hide from information about an adverse event the person is not able to prevent.
The term “doomscrolling” describes the act of endlessly scrolling through bad news on social media and reading every worrisome tidbit that pops up, a habit that unfortunately seems to have become common during the COVID-19 pandemic.
The biology of our brains may play a role in that. Researchers at Washington University School of Medicine in St. Louis have identified specific areas and cells in the brain that become active when an individual is faced with the choice to learn or hide from information about an unwanted aversive event the individual likely has no power to prevent.
The findings, published June 11 in Neuron, could shed light on the processes underlying psychiatric conditions such as obsessive-compulsive disorder and anxiety — not to mention how all of us cope with the deluge of information that is a feature of modern life.
“People’s brains aren’t well equipped to deal with the information age,” said senior author Ilya Monosov, PhD, an associate professor of neuroscience, of neurosurgery and of biomedical engineering.
“People are constantly checking, checking, checking for news, and some of that checking is totally unhelpful. Our modern lifestyles could be resculpting the circuits in our brain that have evolved over millions of years to help us survive in an uncertain and ever-changing world.”
In 2019, studying monkeys, Monosov laboratory members J. Kael White, PhD, then a graduate student, and senior scientist Ethan S. Bromberg-Martin, PhD, identified two brain areas involved in tracking uncertainty about positively anticipated events, such as rewards. Activity in those areas drove the monkeys’ motivation to find information about good things that may happen.
But it wasn’t clear whether the same circuits were involved in seeking information about negatively anticipated events, like punishments. After all, most people want to know whether, for example, a bet on a horse race is likely to pay off big. Not so for bad news.
“In the clinic, when you give some patients the opportunity to get a genetic test to find out if they have, for example, Huntington’s disease, some people will go ahead and get the test as soon as they can, while other people will refuse to be tested until symptoms occur,” Monosov said.
“Clinicians see information-seeking behavior in some people and dread behavior in others.”
To find the neural circuits involved in deciding whether to seek information about unwelcome possibilities, first author Ahmad Jezzini, PhD, and Monosov taught two monkeys to recognize when something unpleasant might be headed their way. They trained the monkeys to recognize symbols that indicated they might be about to get an irritating puff of air to the face.
For example, the monkeys first were shown one symbol that told them a puff might be coming but with varying degrees of certainty. A few seconds after the first symbol was shown, a second symbol was shown that resolved the animals’ uncertainty. It told the monkeys that the puff was definitely coming, or it wasn’t.
The researchers measured whether the animals wanted to know what was going to happen by whether they watched for the second signal or averted their eyes or, in separate experiments, letting the monkeys choose among different symbols and their outcomes.
The findings, published June 11 in Neuron, could shed light on the processes underlying psychiatric conditions such as obsessive-compulsive disorder and anxiety — not to mention how all of us cope with the deluge of information that is a feature of modern life. Image is in the public domain
Much like people, the two monkeys had different attitudes toward bad news: One wanted to know the other preferred not to. The difference in their attitudes toward bad news was striking because they were of like mind when it came to good news. When they were given the option of finding out whether they were about to receive something they liked — a drop of juice — they both consistently chose to find out.
“We found that attitudes toward seeking information about negative events can go both ways, even between animals that have the same attitude about positive rewarding events,” said Jezzini, who is an instructor in neuroscience. “To us, that was a sign that the two attitudes may be guided by different neural processes.”
By precisely measuring neural activity in the brain while the monkeys were faced with these choices, the researchers identified one brain area, the anterior cingulate cortex, that encodes information about attitudes toward good and bad possibilities separately.
They found a second brain area, the ventrolateral prefrontal cortex, that contains individual cells whose activity reflects the monkeys’ overall attitudes: yes for info on either good or bad possibilities vs. yes for intel on good possibilities only.
Understanding the neural circuits underlying uncertainty is a step toward better therapies for people with conditions such as anxiety and obsessive-compulsive disorder, which involve an inability to tolerate uncertainty.
“We started this study because we wanted to know how the brain encodes our desire to know what our future has in store for us,” Monosov said. “We’re living in a world our brains didn’t evolve for. The constant availability of information is a new challenge for us to deal with. I think understanding the mechanisms of information seeking is quite important for society and for mental health at a population level.”
Negative spikes in neurons - Biology
All functions performed by the nervous system—from a simple motor reflex to more advanced functions like making a memory or a decision—require neurons to communicate with one another. While humans use words and body language to communicate, neurons use electrical and chemical signals. Just like a person in a committee, one neuron usually receives and synthesizes messages from multiple other neurons before “making the decision” to send the message on to other neurons.
Nerve Impulse Transmission within a Neuron
For the nervous system to function, neurons must be able to send and receive signals. These signals are possible because each neuron has a charged cellular membrane (a voltage difference between the inside and the outside), and the charge of this membrane can change in response to neurotransmitter molecules released from other neurons and environmental stimuli. To understand how neurons communicate, one must first understand the basis of the baseline or ‘resting’ membrane charge.
Neuronal Charged Membranes
The phospholipid bilayer membrane that surrounds a neuron is impermeable to charged molecules or ions. To enter or exit the neuron, ions must pass through special proteins called ion channels that span the membrane. Ion channels have different configurations: open, closed, and inactive, as illustrated in Figure 1. Some ion channels need to be activated in order to open and allow ions to pass into or out of the cell. These ion channels are sensitive to the environment and can change their shape accordingly. Ion channels that change their structure in response to voltage changes are called voltage-gated ion channels. Voltage-gated ion channels regulate the relative concentrations of different ions inside and outside the cell. The difference in total charge between the inside and outside of the cell is called the membrane potential.
Figure 1. Voltage-gated ion channels open in response to changes in membrane voltage. After activation, they become inactivated for a brief period and will no longer open in response to a signal.
Resting Membrane Potential
A neuron at rest is negatively charged: the inside of a cell is approximately 70 millivolts more negative than the outside (−70 mV, note that this number varies by neuron type and by species). This voltage is called the resting membrane potential it is caused by differences in the concentrations of ions inside and outside the cell. If the membrane were equally permeable to all ions, each type of ion would diffuse across the membrane and the system would reach equilibrium. Because ions cannot simply cross the membrane at will, there are different concentrations of several ions inside and outside the cell, as shown in Figure 2. The difference in the number of positively charged potassium ions (K + ) inside and outside the cell dominates the resting membrane potential. When the membrane is at rest, K + ions accumulate inside the cell due to a net movement with the concentration gradient. The negative resting membrane potential is created and maintained by increasing the concentration of cations outside the cell (in the extracellular fluid) relative to inside the cell (in the cytoplasm). The negative charge within the cell is created by the cell membrane being more permeable to potassium ion movement than sodium ion movement. In neurons, potassium ions are maintained at high concentrations within the cell while sodium ions are maintained at high concentrations outside of the cell. The cell possesses potassium and sodium leakage channels that allow the two cations to diffuse down their concentration gradient. However, the neurons have far more potassium leakage channels than sodium leakage channels. Therefore, potassium diffuses out of the cell at a much faster rate than sodium leaks in. Because more cations are leaving the cell than are entering, this causes the interior of the cell to be negatively charged relative to the outside of the cell. The actions of the sodium potassium pump help to maintain the resting potential, once established. Sodium potassium pumps brings two K + ions into the cell while removing three Na + ions per ATP consumed. As more cations are expelled from the cell than taken in, the inside of the cell remains negatively charged relative to the extracellular fluid. It should be noted that chloride ions (Cl – ) tend to accumulate outside of the cell because they are repelled by negatively-charged proteins within the cytoplasm.
|Ion Concentration Inside and Outside Neurons|
|Ion||Extracellular concentration (mM)||Intracellular concentration (mM)||Ratio outside/inside|
|Organic anions (A−)||—||100|
Figure 2. The (a) resting membrane potential is a result of different concentrations of Na+ and K+ ions inside and outside the cell. A nerve impulse causes Na+ to enter the cell, resulting in (b) depolarization. At the peak action potential, K+ channels open and the cell becomes (c) hyperpolarized.
A neuron can receive input from other neurons and, if this input is strong enough, send the signal to downstream neurons. Transmission of a signal between neurons is generally carried by a chemical called a neurotransmitter. Transmission of a signal within a neuron (from dendrite to axon terminal) is carried by a brief reversal of the resting membrane potential called an action potential. When neurotransmitter molecules bind to receptors located on a neuron’s dendrites, ion channels open. At excitatory synapses, this opening allows positive ions to enter the neuron and results in depolarization of the membrane—a decrease in the difference in voltage between the inside and outside of the neuron. A stimulus from a sensory cell or another neuron depolarizes the target neuron to its threshold potential (-55 mV). Na + channels in the axon hillock open, allowing positive ions to enter the cell (Figure 2). Once the sodium channels open, the neuron completely depolarizes to a membrane potential of about +40 mV. Action potentials are considered an “all-or nothing” event, in that, once the threshold potential is reached, the neuron always completely depolarizes. Once depolarization is complete, the cell must now “reset” its membrane voltage back to the resting potential. To accomplish this, the Na + channels close and cannot be opened. This begins the neuron’s refractory period, in which it cannot produce another action potential because its sodium channels will not open. At the same time, voltage-gated K + channels open, allowing K + to leave the cell. As K + ions leave the cell, the membrane potential once again becomes negative. The diffusion of K + out of the cell actually hyperpolarizes the cell, in that the membrane potential becomes more negative than the cell’s normal resting potential. At this point, the sodium channels will return to their resting state, meaning they are ready to open again if the membrane potential again exceeds the threshold potential. Eventually the extra K + ions diffuse out of the cell through the potassium leakage channels, bringing the cell from its hyperpolarized state, back to its resting membrane potential.
Figure 3. The formation of an action potential can be divided into five steps: (1) A stimulus from a sensory cell or another neuron causes the target cell to depolarize toward the threshold potential. (2) If the threshold of excitation is reached, all Na+ channels open and the membrane depolarizes. (3) At the peak action potential, K+ channels open and K+ begins to leave the cell. At the same time, Na+ channels close. (4) The membrane becomes hyperpolarized as K+ ions continue to leave the cell. The hyperpolarized membrane is in a refractory period and cannot fire. (5) The K+ channels close and the Na+/K+ transporter restores the resting potential.
Figure 4. The action potential is conducted down the axon as the axon membrane depolarizes, then repolarizes.
Myelin and the Propagation of the Action Potential
For an action potential to communicate information to another neuron, it must travel along the axon and reach the axon terminals where it can initiate neurotransmitter release. The speed of conduction of an action potential along an axon is influenced by both the diameter of the axon and the axon’s resistance to current leak. Myelin acts as an insulator that prevents current from leaving the axon this increases the speed of action potential conduction. In demyelinating diseases like multiple sclerosis, action potential conduction slows because current leaks from previously insulated axon areas. The nodes of Ranvier, illustrated in Figure 5 are gaps in the myelin sheath along the axon. These unmyelinated spaces are about one micrometer long and contain voltage-gated Na + and K + channels. Flow of ions through these channels, particularly the Na + channels, regenerates the action potential over and over again along the axon. This ‘jumping’ of the action potential from one node to the next is called saltatory conduction. If nodes of Ranvier were not present along an axon, the action potential would propagate very slowly since Na + and K + channels would have to continuously regenerate action potentials at every point along the axon instead of at specific points. Nodes of Ranvier also save energy for the neuron since the channels only need to be present at the nodes and not along the entire axon.
Figure 5. Nodes of Ranvier are gaps in myelin coverage along axons. Nodes contain voltage-gated K+ and Na+ channels. Action potentials travel down the axon by jumping from one node to the next.
The synapse or “gap” is the place where information is transmitted from one neuron to another. Synapses usually form between axon terminals and dendritic spines, but this is not universally true. There are also axon-to-axon, dendrite-to-dendrite, and axon-to-cell body synapses. The neuron transmitting the signal is called the presynaptic neuron, and the neuron receiving the signal is called the postsynaptic neuron. Note that these designations are relative to a particular synapse—most neurons are both presynaptic and postsynaptic. There are two types of synapses: chemical and electrical.
When an action potential reaches the axon terminal it depolarizes the membrane and opens voltage-gated Na + channels. Na + ions enter the cell, further depolarizing the presynaptic membrane. This depolarization causes voltage-gated Ca 2+ channels to open. Calcium ions entering the cell initiate a signaling cascade that causes small membrane-bound vesicles, called synaptic vesicles, containing neurotransmitter molecules to fuse with the presynaptic membrane. Synaptic vesicles are shown in Figure 6, which is an image from a scanning electron microscope.
Figure 6. This pseudocolored image taken with a scanning electron microscope shows an axon terminal that was broken open to reveal synaptic vesicles (blue and orange) inside the neuron. (credit: modification of work by Tina Carvalho, NIH-NIGMS scale-bar data from Matt Russell)
Fusion of a vesicle with the presynaptic membrane causes neurotransmitter to be released into the synaptic cleft, the extracellular space between the presynaptic and postsynaptic membranes, as illustrated in Figure 7. The neurotransmitter diffuses across the synaptic cleft and binds to receptor proteins on the postsynaptic membrane.
Figure 7. Communication at chemical synapses requires release of neurotransmitters. When the presynaptic membrane is depolarized, voltage-gated Ca2+ channels open and allow Ca2+ to enter the cell. The calcium entry causes synaptic vesicles to fuse with the membrane and release neurotransmitter molecules into the synaptic cleft. The neurotransmitter diffuses across the synaptic cleft and binds to ligand-gated ion channels in the postsynaptic membrane, resulting in a localized depolarization or hyperpolarization of the postsynaptic neuron.
The binding of a specific neurotransmitter causes particular ion channels, in this case ligand-gated channels, on the postsynaptic membrane to open. Neurotransmitters can either have excitatory or inhibitory effects on the postsynaptic membrane, as detailed in. For example, when acetylcholine is released at the synapse between a nerve and muscle (called the neuromuscular junction) by a presynaptic neuron, it causes postsynaptic Na + channels to open. Na + enters the postsynaptic cell and causes the postsynaptic membrane to depolarize. This depolarization is called an excitatory postsynaptic potential (EPSP) and makes the postsynaptic neuron more likely to fire an action potential. Release of neurotransmitter at inhibitory synapses causes inhibitory postsynaptic potentials (IPSPs), a hyperpolarization of the presynaptic membrane. For example, when the neurotransmitter GABA (gamma-aminobutyric acid) is released from a presynaptic neuron, it binds to and opens Cl – channels. Cl – ions enter the cell and hyperpolarizes the membrane, making the neuron less likely to fire an action potential.
Once neurotransmission has occurred, the neurotransmitter must be removed from the synaptic cleft so the postsynaptic membrane can “reset” and be ready to receive another signal. This can be accomplished in three ways: the neurotransmitter can diffuse away from the synaptic cleft, it can be degraded by enzymes in the synaptic cleft, or it can be recycled (sometimes called reuptake) by the presynaptic neuron. Several drugs act at this step of neurotransmission. For example, some drugs that are given to Alzheimer’s patients work by inhibiting acetylcholinesterase, the enzyme that degrades acetylcholine. This inhibition of the enzyme essentially increases neurotransmission at synapses that release acetylcholine. Once released, the acetylcholine stays in the cleft and can continually bind and unbind to postsynaptic receptors.
|Neurotransmitter Function and Location|
|Acetylcholine||—||CNS and/or PNS|
|Biogenic amine||Dopamine, serotonin, norepinephrine||CNS and/or PNS|
|Amino acid||Glycine, glutamate, aspartate, gamma aminobutyric acid||CNS|
|Neuropeptide||Substance P, endorphins||CNS and/or PNS|
While electrical synapses are fewer in number than chemical synapses, they are found in all nervous systems and play important and unique roles. The mode of neurotransmission in electrical synapses is quite different from that in chemical synapses. In an electrical synapse, the presynaptic and postsynaptic membranes are very close together and are actually physically connected by channel proteins forming gap junctions. Gap junctions allow current to pass directly from one cell to the next. In addition to the ions that carry this current, other molecules, such as ATP, can diffuse through the large gap junction pores.
There are key differences between chemical and electrical synapses. Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is unidirectional. Signaling in electrical synapses, in contrast, is virtually instantaneous (which is important for synapses involved in key reflexes), and some electrical synapses are bidirectional. Electrical synapses are also more reliable as they are less likely to be blocked, and they are important for synchronizing the electrical activity of a group of neurons. For example, electrical synapses in the thalamus are thought to regulate slow-wave sleep, and disruption of these synapses can cause seizures.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron, but often multiple presynaptic inputs must create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential. This process is called summation and occurs at the axon hillock, as illustrated in Figure 8. Additionally, one neuron often has inputs from many presynaptic neurons—some excitatory and some inhibitory—so IPSPs can cancel out EPSPs and vice versa. It is the net change in postsynaptic membrane voltage that determines whether the postsynaptic cell has reached its threshold of excitation needed to fire an action potential. Together, synaptic summation and the threshold for excitation act as a filter so that random “noise” in the system is not transmitted as important information.
Figure 8. A single neuron can receive both excitatory and inhibitory inputs from multiple neurons, resulting in local membrane depolarization (EPSP input) and hyperpolarization (IPSP input). All these inputs are added together at the axon hillock. If the EPSPs are strong enough to overcome the IPSPs and reach the threshold of excitation, the neuron will fire.
Amyotrophic lateral sclerosis (ALS, also called Lou Gehrig’s Disease) is a neurological disease characterized by the degeneration of the motor neurons that control voluntary movements. The disease begins with muscle weakening and lack of coordination and eventually destroys the neurons that control speech, breathing, and swallowing in the end, the disease can lead to paralysis. At that point, patients require assistance from machines to be able to breathe and to communicate. Several special technologies have been developed to allow “locked-in” patients to communicate with the rest of the world. One technology, for example, allows patients to type out sentences by twitching their cheek. These sentences can then be read aloud by a computer.
A relatively new line of research for helping paralyzed patients, including those with ALS, to communicate and retain a degree of self-sufficiency is called brain-computer interface (BCI) technology and is illustrated in Figure 9. This technology sounds like something out of science fiction: it allows paralyzed patients to control a computer using only their thoughts. There are several forms of BCI. Some forms use EEG recordings from electrodes taped onto the skull. These recordings contain information from large populations of neurons that can be decoded by a computer. Other forms of BCI require the implantation of an array of electrodes smaller than a postage stamp in the arm and hand area of the motor cortex. This form of BCI, while more invasive, is very powerful as each electrode can record actual action potentials from one or more neurons. These signals are then sent to a computer, which has been trained to decode the signal and feed it to a tool—such as a cursor on a computer screen. This means that a patient with ALS can use e-mail, read the Internet, and communicate with others by thinking of moving his or her hand or arm (even though the paralyzed patient cannot make that bodily movement). Recent advances have allowed a paralyzed locked-in patient who suffered a stroke 15 years ago to control a robotic arm and even to feed herself coffee using BCI technology.
Despite the amazing advancements in BCI technology, it also has limitations. The technology can require many hours of training and long periods of intense concentration for the patient it can also require brain surgery to implant the devices.
Figure 9. With brain-computer interface technology, neural signals from a paralyzed patient are collected, decoded, and then fed to a tool, such as a computer, a wheelchair, or a robotic arm.
-  M. Helmstaedter, K. L. Briggman, S. C. Turaga, V. Jain, H. S. Seung, and W. Denk, “Connectomic reconstruction of the inner plexiform layer in the mouse retina,” Nature, vol. 500, pp. 168–174, Aug. 2013.
-  H. Zeng and J. R. Sanes, “Neuronal cell-type classification: challenges, opportunities and the path forward,” Nature Reviews Neuroscience, vol. 18, no. 9, p. 530, 2017.
-  R. E. Marc, B. W. Jones, C. B. Watt, J. R. Anderson, C. Sigulinsky, and S. Lauritzen, “Retinal connectomics: towards complete, accurate networks,” Progress in Retinal and Eye Research, vol. 37, pp. 141–162, 2013.
-  H. S. Seung and U. Sümbül, “Neuronal cell types and connectivity: lessons from the retina,” Neuron, vol. 83, no. 6, pp. 1262–1272, 2014.
-  J. R. Sanes and R. H. Masland, “The types of retinal ganglion cells: current status and implications for neuronal classification,” Annual Review of Neuroscience, vol. 38, pp. 221–246, 2015.
-  J. B. Demb and J. H. Singer, “Functional circuitry of the retina,” Annual Review of Vision Science, vol. 1, pp. 263–289, 2015.
-  E. Chichilnisky, “A simple white noise analysis of neuronal light responses,” Network: Computation in Neural Systems, vol. 12, no. 2, pp. 199–213, 2001.
-  J. W. Pillow, J. Shlens, L. Paninski, A. Sher, A. M. Litke, E. Chichilnisky, and E. P. Simoncelli, “Spatio-temporal correlations and visual signalling in a complete neuronal population,” Nature, vol. 454, no. 7207, p. 995, 2008.
-  J. M. McFarland, Y. Cui, and D. A. Butts, “Inferring nonlinear neuronal computation based on physiologically plausible inputs,” PLoS Computational Biology, vol. 9, no. 7, p. e1003143, jul 2013.
-  S. Song, P. J. Sjöström, M. Reigl, S. Nelson, and D. B. Chklovskii, “Highly nonrandom features of synaptic connectivity in local cortical circuits,” PLoS Biology, vol. 3, no. 3, pp. 507–519, 2005.
-  X. Jiang, S. Shen, C. R. Cadwell, P. Berens, F. Sinz, A. S. Ecker, S. Patel, and A. S. Tolias, “Principles of connectivity among morphologically defined cell types in adult neocortex,” Science, vol. 350, no. 6264, p. aac9462, 2015.
-  J. K. Liu, H. M. Schreyer, A. Onken, F. Rozenblit, M. H. Khani, V. Krishnamoorthy, S. Panzeri, and T. Gollisch, “Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization,” Nature Communications, vol. 8, no. 1, p. 149, 2017.
-  D. D. Lee and H. S. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature, vol. 401, no. 6755, pp. 788–791, oct 1999.
-  X. Zhao, X. Li, Z. Zhang, C. Shen, Y. Zhuang, L. Gao, and X. Li, “Scalable linear visual feature learning via online parallel nonnegative matrix factorization,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2628–2642, dec 2016.
-  M. Ye, Y. Qian, and J. Zhou, “Multitask sparse nonnegative matrix factorization for joint spectral–spatial hyperspectral imagery denoising,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2621–2639, 2015.
-  K. Kwon, J. W. Shin, and N. S. Kim, “NMF-based speech enhancement using bases update,” IEEE Signal Processing Letters, vol. 22, no. 4, pp. 450–454, apr 2015.
-  N. Guan, D. Tao, Z. Luo, and B. Yuan, “NeNMF: an optimal gradient method for nonnegative matrix factorization,” IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 2882–2898, 2012.
-  B. Gao, W. L. Woo, and B. W. Ling, “Machine learning source separation using maximum a posteriori nonnegative matrix factorization,” IEEE Transactions on Cybernetics, vol. 44, no. 7, pp. 1169–1179, 2014.
-  X. Pei, T. Wu, and C. Chen, “Automated graph regularized projective nonnegative matrix factorization for document clustering,” IEEE Transactions on Cybernetics, vol. 44, no. 10, pp. 1821–1831, 2014.
-  T. Blumensath, “Directional clustering through matrix factorization,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 10, pp. 2095–2107, 2016.
-  H. Wang, F. Nie, H. Huang, and F. Makedon, “Fast nonnegative matrix tri-factorization for largescale data coclustering,” in
IJCAI Proceedings-International Joint Conference on Artificial Intelligence
A. Onken, J. K. Liu, P. C. R. Karunasekara, I. Delis, T. Gollisch, and S. Panzeri, “Using matrix and tensor factorizations for the singletrial analysis of population spike trains,”
V. Zampini, J. K. Liu, M. A. Diana, P. P. Maldonado, N. Brunel, and S. Dieudonné, “Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit,”
D. L. Yamins and J. J. DiCarlo, “Using goaldriven deep learning models to understand sensory cortex,”
Negative Feedback Signals
Since neurons constantly generate only one axon and other minor neurites that never become axons, negative feedback signals play an important role in the formation of a single axon, and multiple dendrites during neuronal development (Arimura and Kaibuchi, 2007 Takano et al., 2015). Several models of negative feedback signals have been proposed (Inagaki et al., 2011 Takano et al., 2015 Schelski and Bradke, 2017 Yogev and Shen, 2017). cAMP and cGMP show antagonistic actions on each other during neuronal polarization (Shelly et al., 2010). Local elevation of cAMP level induces axon specification through PKA activation, whereas the cGMP level is increased by reducing the amount of cAMP in other minor neurites and then leads to dendritic specification (Shelly et al., 2010). However, it remains unclear how the cAMP elevation in the nascent axon regulates the cGMP level in all of the other minor neurites. It has also been proposed that there is a winner-take-all model for the establishment of neuronal polarity (Inagaki et al., 2011 Schelski and Bradke, 2017). As the amount of growth-relating factors are limited, local accumulation of these factors in the nascent axon deplete them in all of the other minor neurites. In turn, all of the other minor neurites could not become axons (Inagaki et al., 2011 Schelski and Bradke, 2017). More recently, a spatiotemporal long-range negative feedback signal for guaranteeing the proper neuronal polarization has been identified (Takano et al., 2017). The negative feedback signal is mediated by unique long-range Ca 2+ waves, which are generated by NT-3 and propagate from the growing nascent axon to the cell body (Takano et al., 2017). The long-range Ca 2+ waves subsequently activate calmodulin-dependent protein kinase I (CaMKI) at the cell body (Takano et al., 2017). CaMKI induces phosphorylation and activation of a RhoA-specific GEF, GEF-H1, and thereby activates RhoA and its effector Rho-kinase at the cell body (Takano et al., 2017). RhoA and Rho-kinase are well known as key negative regulators of neurogenesis through modulating the actin cytoskeleton and myosin-based contractility in several cell lines (Da Silva et al., 2003 Conde et al., 2010). Interestingly, photoactivation of RhoA or Rho-kinase by an optogenetic approach, LOV2 trap and release of the protein (LOVTRAP), in the cell body specifically inhibits minor neurite elongation in polarized neurons (Takano et al., 2017). Additionally, computational modeling has shown that active Rho-kinase spreads from the cell body into the minor neurites but not into the axons for preventing multiple axonal formation (Takano et al., 2017). Consistently, inhibition of Rho-kinase induces minor neurite elongation that develops into multiple axons (Takano et al., 2017). These results indicate the polarized activation of RhoA/Rho-kinase is necessary for generation of the single axon and multiple dendrites during neuronal development (Gonzalez-Billault et al., 2012 Takano et al., 2017). In the developing cortex, inhibition of RhoA or Rho-kinase by the expression of the dominant negative mutant impairs the MP-to-BP transition, and neuronal migration (Xu et al., 2015). The expression of a phospho-mimic mutant of GEF-H1, which leads to RhoA activation, also disrupts the MP-to-BP transition and neuronal migration, indicating the polarized RhoA/Rho-kinase activity is essential for neuronal polarization and neuronal migration in vivo (Xu et al., 2015 Takano et al., 2017). Rho-kinase maintains RhoA activation through phosphorylation and inactivation of p190RhoGAP (Mori et al., 2009). Importantly, Rho-kinase can inactivate Rac1 through the disruption of Par complex and inactivation of STEF in a phosphorylation-dependent manner (Takefuji et al., 2007 Nakayama et al., 2008). Thus, the long-range Ca 2+ waves/CaMKI/GEF-H1/RhoA/Rho-kinase pathway represents a negative feedback signal that functions to repress the positive feedback loop in all minor neurites to inhibit multiple axonal formation and determine dendritic specification (Arimura and Kaibuchi, 2007 Takano et al., 2015, 2017 Figure 2). Together, Rac1-dependent positive feedback signals in the nascent axon and RhoA/Rho-kinase-dependent negative feedback signals in all other minor neurites guarantee proper neuronal polarization (Figure 2B).
The Brain’s Biology: A Negative Feedback Loop System
Are you ready for a challenge? I want you to make a list of all of the things that your child or children have done right today. Go ahead, pull out a blank piece of paper or a blank computer screen and begin listing everything where your child did and behaved as you wanted him to. I’ll wait while you take the time to actually complete this task.
Okay, now list the opposite. On the other side of the paper, or after creating a page break, list all of the things where your child did not do what you asked, did not listen to you, misbehaved – times when you felt annoyed, upset or aggravated.
For those of you reluctant to take the extra step of actually making the list, I guarantee you that making this little effort will have greater impact and help your learning.
Our brain is a feedback loop system. In fact, it isn’t just the brain that is a feedback loop system. Every system and cell in our body is a feedback loop system. For the purpose of understanding life on a grand level, let’s talk about understanding the implications of this feedback loop system.
The human brain is a negative feedback loop systems. This means that whenever there is a difference between what a person experiences in reality that is different from the ideal set point established by this person’s brain, an urge to behave to correct the situation is created by the brain. For example, each person has a comfortable room temperature as his ideal set point. When the room temperature dips below the ideal, the person will take action to correct the situation and re-establish the environment to match the comfortable room temperature set point established by this person. The creativity and adaptability of being human means you can choose from a wide variety of solutions to increase your warmth. You can put on warmer clothes. You can exercise, increasing your own internal temperature. You can build a fire, or turn up the heat, or sit in a sunny spot in the room. But any action you take is generated by the signal your brain gives you that what you want does not match what you are getting.
The important point to understand is that your brain is set up to notice what is wrong to notice the exceptions, the mismatches, the painful areas that are out of order. It is the mismatch between what you want and what you are getting that creates the signal for you to take action.
Your brain does not notice when what you want matches what you are getting. You don’t pay attention. Because there is no signal generated by your brain, you aren’t even aware of it.
There are exceptions. When you finally get what you want after being out of balance for an extended time, the relief of the match feels wonderful. Remember the joy and relief you have felt when you finally entered a warm room after being cold for too long? Sipping a hot beverage, snuggled up next to a fire after being outside in the cold for several hours, feels delightful. This match is a relief and is very much part of your awareness and gratitude.
But, are you aware of the temperature in the room you are in right now? If you are too cold or too warm, then you probably are aware of it. But if you are in a comfortable room, you haven’t even noticed the temperature. Your brain functions to bring your awareness and action to situations when there is a mismatch – not when there is comfort, satisfaction, and a match.
Now let’s apply this idea to your interactions and relationship with children. As a classroom teacher, you are very aware of the children who are misbehaving in your classroom. Are you aware of the children who are cooperating, learning, and engaged? Don’t despair if you are only paying attention to the misbehaving children. It is how your brain functions. Your brain’s biology signals you into action when misbehaving children are present. Your brain’s biology gives you no notice of well-behaved, cooperative children. They go unnoticed.
Because children’s brains function the same way, your students may not be aware of what they are doing well, where they are achieving, and where they are being successful. In order for this to happen, they have to go against their brain’s biology and extend extra effort to find the moments and areas where their achievement matches their desired outcome. Looking for successful accomplishments, especially small and minor ones, is not part of our nature.
Ask a child to self-evaluate as she aims for successful achievements and attainment. Going one step further by asking her what she did to be successful helps her learn, internalize, and grow to master the effective skills and habits she is developing. Does she know what she can do to have even more success? Although it may feel as if things just turned out well without any effort on the child’s part, asking children to notice what they did well will maximize their learning because their brain is not going to automatically notice when there is a match. Without your helpful intervention, the brain will only notice the mismatch.
Are you aware of all of the ways your child is listening, is cooperating, and is doing just what you want? If you are, then this is probably a habit that took time and effort for you to develop.
At the beginning of this article, I asked you to list the delightful matches between what you wanted and what you were getting from your child. I also asked you to list the mismatches where what you wanted from your child was different from what your were getting. Which of these two lists was easier for you to make? If you’re like most people, the mismatches were quicker and easier for you to identify than the matches. Why? Because the biology of our brain is a negative feedback loop, giving us feedback and urging us to behave when we are not getting what we want.
With this powerful information you can make dramatic changes. For the next week, start paying attention to all of the ways that life is working out for you. For instance, the next time you drive to work, notice how many other drivers are cooperating with you, driving safely, everyone free from an accident and danger. There may be one or two drivers who are the unfortunate exception, but the vast majority of people on the road with you are safe, cooperative drivers.
For the next week, notice all the ways your child is doing well, cooperating, and helping, being pleasant, friendly, and loving. There may be moments when he sasses you or she whines, but the vast majority of your life together is filled with cooperative and pleasant moments.
Teachers, the next time you enter the staff room, celebrate with your colleagues about the 22 students who were working cooperatively with you on your most recent lesson rather than the one or two students who disrupted.
Are you getting the picture? You have to go against your biology, against your brain, to notice all of the matches – the pleasant, stress-free moments in your life and with your child. As you practice this skill more and more, it becomes a habit – one that will bring you joy.
This is a powerful skill to teach children as well. When children notice their success, happiness, and achievement, and attribute it to their own effective behaviors, they understand that what they do on a daily basis helps them meet their needs responsibly. They understand that their happiness is up to them and not dependent on anyone else. What a great gift of understanding to give to a child!