Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area

In the paper

“Thus, both monkeys learned how to perform the task in early sessions and soon could express the visuomotor association for high-coherence stimuli with few or no errors.”

In the paper

“Throughout training, on trials in which the monkey selected the saccade target in the neuron’s response field LIP activity tended to increase gradually during motion viewing, stay elevated during the subsequent delay period and then increase just prior to saccade onset.”

In the paper

“Some of these parameters changed with training, but none were consistently correlated with the changes in LIP responsiveness over the course of training for both monkeys (Fig. 5 and Table S1).”

In the paper

“Neurometric thresholds were, on average, ~4% better during versus before training, but the differences were not significant (monkey C: geometric mean threshold coherence before training = 25.9%, during training = 21.0%, Mann-Whitney U test p=0.1964; monkey Z: before = 21.1%; during = 18.4%, p=0.4762).”

In the paper

“The peri-saccadic activity tended to be smaller in the first ~15 sessions (average activity from −0.5 to −0.1s before saccade onset=18.6 spikes/s from sessions 1–15 and 31.3 spikes/s from sessions 16–160, t-test p=0.0157 for monkey C; 27.0 spikes/s from sessions 1–15 and 48.6 sp/s from sessions 16–130, p=0.0024 for monkey Z) but then remained relatively stable throughout the rest of training (”

In the paper

“For both monkeys, the value of this motion-sensitive term grew as a function of training session in a similar manner for data from behaviour and LIP but not MT (Fig. 6b,c; monkey C: correlation coefficient between MT and behaviour r=0.03, H0: r=0 using Fisher’s Z transformation, p=0.7874; LIP and behaviour r=0.59, p<10−12; monkey Z: MT and behaviour r=−0.14, p=0.2911; LIP and behaviour r=0.60, p<”

In the paper

“The pattern of coherence-specific changes in LIP was similar to the pattern of coherence-specific behavioural improvements: both the rate of rise of stimulus-driven LIP responses and discrimination performance increased as a function of training session for most non-zero coherences, with greater increases for higher coherences (H0: slope of a linear regression between session number and either”

In the paper

“In MT, individual neurons responded similarly to motion stimuli before and throughout training, with, on average, a sensitivity that was similar to that of trained monkeys.”

In the paper

“Indeed, throughout training, performance improved significantly for all non-zero coherences for monkey C and for 12.8–99.9% coherence for monkey Z (linear regression of percent correct per coherence with training session, H0: slope=0, p<0.05).”

In the paper

“However, a small number of simultaneously recorded pairs of MT neurons provide preliminary evidence that the degree of correlation is similar before (mean±SEM correlation coefficient r=0.16±0.06, n=8) and during (r=0.18±0.04, n=9) training and does not increase over the course of training (linear regression, H0: slope=0, p=0.5728).”

In the paper

“we showed that both behaviour and LIP responses continued to evolve well after the visuomotor association was established, together reflecting improved sensitivity to weak motion.”

In the paper

“To further quantify improvements in performance with training, we used a time-dependent cumulative Weibull function (Eq. 1 and solid lines in Fig. 2a,b) to estimate the discrimination threshold, which is the motion strength at which the monkey achieved ~82% correct for a 1-s viewing duration, for each session. This function takes into account associative (high-coherence) errors (λ in Eq. 1) and”

In the paper

“In trained monkeys, MT and LIP are thought to play different but complementary roles in forming the direction decision: MT (possibly in tandem with other motion-sensitive areas like the middle superior temporal area, or MST) provides sensory evidence used to form the decision, whereas LIP (possibly in tandem with other sensory-oculomotor areas like the FEF and superior colliculus) accumulates and”

What the sources say

• Not checked yetcites [23] Gold, J.I. & Shadlen, M.N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007). source

In the paper

“A straightforward interpretation of this result is that training does not affect the representation of sensory evidence in MT directly but effectively scales its output, providing increasingly sensitive evidence to the decision variable in LIP used to guide behaviour.”

In the paper

“Within this constraint, we sought to minimize changes in the stimulus configuration across sessions by selecting neurons with consistent tuning properties, including receptive field (RF) location and direction preference of MT neurons and response field location of LIP neurons (Fig. S1).”

In the paper

“which is consistent with the idea that perceptual learning can be specific by virtue of what is learned (in this case, the LIP decision variable) and need not involve changes in the sensory representation (direction-selective responses in area MT)3.”

What the sources say

• Not checked yetcites [3] Mollon, J.D. & Danilova, M.V. Three remarks on perceptual learning. Spat. Vis. 10, 51–58 (1996). source

In the paper

“Perceptual learning is typically specific to the stimulus attributes used during training, including motion direction in a direction-discrimination task33.”

What the sources say

• Not checked yetcites [33] Ball, K. & Sekuler, R. A specific and enduring improvement in visual motion discrimination. Science 218, 697–698 (1982). source

In the paper

“Because these neurons were selected based on spatially tuned pre-saccadic activity (see Methods, Fig. S5), this result implies that training both established and then shaped the sensory-driven responses in these sensory-motor neurons.”

In the paper

“Training occurred only while the responses of at least one MT or LIP neuron were isolated and recorded, allowing us to make direct, session-by-session comparisons of behavioural and neuronal performance as training progressed.”

In the paper

“larger effects have been found in V1 of human subjects using fMRI36”

What the sources say

• Not checked yetcites [36] Furmanski, C.S., Schluppeck, D. & Engel, S.A. Learning strengthens the response of primary visual cortex to simple patterns. Curr. Biol. 14, 573–578 (2004). source

In the paper

“the established role of MT in task performance16–19”

What the sources say

• Not checked yetcites [16] Britten, K.H., Shadlen, M.N., Newsome, W.T. & Movshon, J.A. The analysis of visual motion: a comparison of neuronal and psychophysical performance. J. Neurosci. 12, 4745–4765 (1992). source
• Not checked yetcites [17] Britten, K.H., Newsome, W.T., Shadlen, M.N., Celebrini, S. & Movshon, J.A. A relationship between behavioral choice and the visual responses of neurons in macaque MT. Vis. Neurosci. 13, 87–100 (1996). source
• Not checked yetcites [18] Newsome, W.T. & Pare, E.B. A selective impairment of motion perception following lesions of the middle temporal visual area (MT). J. Neurosci. 8, 2201–2211 (1988). source
• Not checked yetcites [19] Salzman, C.D., Britten, K.H. & Newsome, W.T. Cortical microstimulation influences perceptual judgments of motion direction. Nature 346, 174–177 (1990). source

In the paper

“Of the learning-induced changes that have been found previously in V1, attentional modulation appears to play a primary role8.”

What the sources say

• Not checked yetcites [8] Crist, R.E., Li, W. & Gilbert, C.D. Learning to see: experience and attention in primary visual cortex. Nat. Neurosci. 4, 519–525 (2001). source

In the paper

“Our results also further distinguish early visual cortical areas from primary somatosensory and auditory cortices, which in both monkeys and humans can show dramatic changes with perceptual learning5, 6, 37–39.”

What the sources say

• Not checked yetcites [5] Recanzone, G.H., Schreiner, C.E. & Merzenich, M.M. Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys. J. Neurosci. 13, 87–103 (1993). source
• Not checked yetcites [6] Recanzone, G.H., Merzenich, M.M., Jenkins, W.M., Grajski, K.A. & Dinse, H.R. Topographic reorganization of the hand representation in cortical area 3b owl monkeys trained in a frequency-discrimination task. J. Neurophysiol. 67, 1031–1056 (1992). source
• Not checked yetcites [37] Pleger, B. et al. Functional imaging of perceptual learning in human primary and secondary somatosensory cortex. Neuron 40, 643–653 (2003). source
• Not checked yetcites [38] Bao, S., Chang, E.F., Woods, J. & Merzenich, M.M. Temporal plasticity in the primary auditory cortex induced by operant perceptual learning. Nat. Neurosci. 7, 974–981 (2004). source
• Not checked yetcites [39] Blake, D.T., Heiser, M.A., Caywood, M. & Merzenich, M.M. Experience-dependent adult cortical plasticity requires cognitive association between sensation and reward. Neuron 52, 371–381 (2006). source

In the paper

“LIP plays a multitude of cognitive and sensory-motor roles that could, in principle, change during training and account for the changes in LIP responses during motion viewing 20–22.”

What the sources say

• Not checked yetcites [20] Colby, C.L. & Goldberg, M.E. Space and attention in parietal cortex. Annu. Rev. Neurosci. 22, 319–349 (1999). source
• Not checked yetcites [21] Platt, M.L. & Glimcher, P.W. Neural correlates of decision variables in parietal cortex. Nature 400, 233–238 (1999). source
• Not checked yetcites [22] Snyder, L.H., Batista, A.P. & Andersen, R.A. Intention-related activity in the posterior parietal cortex: a review. Vision Res. 40, 1433–1441 (2000). source

In the paper

“In trained monkeys, multiple brain areas including LIP, the superior colliculus and parts of the prefrontal cortex including the FEF exhibit similar sensory-motor responses during performance of the discrimination task24, 25, 27, 28.”

What the sources say

• Not checked yetcites [24] Shadlen, M.N. & Newsome, W.T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J. Neurophysiol. 86, 1916–1936 (2001). source
• Not checked yetcites [25] Roitman, J.D. & Shadlen, M.N. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22, 9475–9489 (2002). source
• Not checked yetcites [27] Horwitz, G.D. & Newsome, W.T. Separate signals for target selection and movement specification in the superior colliculus. Science 284, 1158–1161 (1999). source
• Not checked yetcites [28] Kim, J.N. & Shadlen, M.N. Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nat. Neurosci. 2, 176–185 (1999). source